{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Weighted time series forecasting\n",
    "\n",
    "In many real-world scenarios, historical data is available for forecasting, but not all of it is reliable. For example, IoT sensors capture raw data from the physical world, but they are often prone to failure, malfunction, and attrition due to harsh deployment environments, leading to unusual or erroneous readings. Similarly, factories may shut down for maintenance, repair, or overhaul, resulting in gaps in the data. The Covid-19 pandemic has also affected population behavior, impacting many time series such as production, sales, and transportation.\n",
    "\n",
    "The presence of unreliable or unrepresentative values in the data history poses a significant challenge, as it hinders model learning. However, most forecasting algorithms require complete time series data, making it impossible to remove these observations. An alternative solution is to reduce the weight of the affected observations during model training. This document demonstrates how **skforecast** makes it easy to implement this strategy with two examples."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"admonition note\" name=\"html-admonition\" style=\"background: rgba(0,184,212,.1); padding-top: 0px; padding-bottom: 6px; border-radius: 8px; border-left: 8px solid #00b8d4; border-color: #00b8d4; padding-left: 10px; padding-right: 10px;\">\n",
    "\n",
    "<p class=\"title\">\n",
    "    <i style=\"font-size: 18px; color:#00b8d4;\"></i>\n",
    "    <b style=\"color: #00b8d4;\">&#9998 Note</b>\n",
    "</p>\n",
    "\n",
    "The examples that follow demonstrate how a portion of the time series can be excluded from model training by assigning it a weight of zero. However, the use of weights extends beyond the inclusion or exclusion of observations and can also balance the degree of influence that each observation has on the forecasting model. For instance, an observation assigned a weight of 10 will have ten times more impact on the model training than an observation assigned a weight of 1.\n",
    "\n",
    "</div>"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"admonition note\" name=\"html-admonition\" style=\"background: rgba(255,145,0,.1); padding-top: 0px; padding-bottom: 6px; border-radius: 8px; border-left: 8px solid #ff9100; border-color: #ff9100; padding-left: 10px; padding-right: 10px\">\n",
    "\n",
    "<p class=\"title\">\n",
    "    <i style=\"font-size: 18px; color:#ff9100; border-color: #ff1744;\"></i>\n",
    "    <b style=\"color: #ff9100;\"> <span style=\"color: #ff9100;\">&#9888;</span> Warning</b>\n",
    "</p>\n",
    "\n",
    "In most gradient boosting implementations, such as LightGBM, XGBoost, and CatBoost, samples with zero weight are typically excluded when calculating gradients and Hessians. However, these samples are still taken into account when constructing the feature histograms, which can result in a model that differs from one trained without zero-weighted samples. For more information on this issue, please refer to <a href=\"https://github.com/microsoft/LightGBM/issues/5553\">this GitHub issue</a>.\n",
    "\n",
    "</div>"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Libraries and data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Libraries\n",
    "# ==============================================================================\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.linear_model import Ridge\n",
    "from skforecast.recursive import ForecasterRecursive\n",
    "from skforecast.model_selection import TimeSeriesFold, backtesting_forecaster\n",
    "from skforecast.plot import set_dark_theme"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>production</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2012-01-01</th>\n",
       "      <td>375.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-02</th>\n",
       "      <td>474.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-03</th>\n",
       "      <td>573.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-04</th>\n",
       "      <td>539.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-05</th>\n",
       "      <td>445.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            production\n",
       "date                  \n",
       "2012-01-01       375.1\n",
       "2012-01-02       474.5\n",
       "2012-01-03       573.9\n",
       "2012-01-04       539.5\n",
       "2012-01-05       445.4"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data download\n",
    "# ==============================================================================\n",
    "url = (\n",
    "    'https://raw.githubusercontent.com/skforecast/skforecast-datasets/refs/heads/'\n",
    "    'main/data/energy_production_shutdown.csv'\n",
    ")\n",
    "data = pd.read_csv(url, sep=',')\n",
    "\n",
    "# Data preprocessing\n",
    "# ==============================================================================\n",
    "data['date'] = pd.to_datetime(data['date'], format='%Y-%m-%d')\n",
    "data = data.set_index('date')\n",
    "data = data.asfreq('D')\n",
    "data = data.sort_index()\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dates train : 2012-01-01 00:00:00 --- 2013-12-31 00:00:00   (n=731)\n",
      "Dates test  : 2014-01-01 00:00:00 --- 2014-12-30 00:00:00   (n=364)\n"
     ]
    }
   ],
   "source": [
    "# Split data into train-val-test\n",
    "# ==============================================================================\n",
    "data = data.loc['2012-01-01 00:00:00': '2014-12-30 23:00:00']\n",
    "end_train = '2013-12-31 23:59:00'\n",
    "data_train = data.loc[: end_train, :]\n",
    "data_test  = data.loc[end_train:, :]\n",
    "\n",
    "print(\n",
    "    f\"Dates train : {data_train.index.min()} --- {data_train.index.max()}   \"\n",
    "    f\"(n={len(data_train)})\"\n",
    ")\n",
    "print(\n",
    "    f\"Dates test  : {data_test.index.min()} --- {data_test.index.max()}   \"\n",
    "    f\"(n={len(data_test)})\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAApQAAAFBCAYAAADJ1D89AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjMsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvZiW1igAAAAlwSFlzAAAPYQAAD2EBqD+naQAA0ilJREFUeJzsXQWYHFXWvdUybpGJG4QkBBISSJDgEGBxFtgfh4VFF/cl+LL44uzizgKLL77A4hIkSEKQuOtkJuPSVv93X71b/ep1Vct4z9zzfUlPd1W9emXvnTrXDBgwxQQGg8FgMBgMBqOV8LV2QwaDwWAwGAwGA8GEksFgMBgMBoPRJjChZDAYDAaDwWC0CUwoGQwGg8FgMBhtAhNKBoPBYDAYDEabwISSwWAwGAwGg9EmMKFkMBgMBoPBYLQJTCgZDAaDwWAwGG0CE0oGg8FgMBgMRpvAhJLBYDB6AKZNnQCrf3wDLjrjaOguGDZkgOjTnded39VdYTAYHYxAR++AwWB0T+BEnwqHnzIDZs6a2yn9YWTvffTlrJ/gD6dc3tVdYTAYXQgmlAxGL8ftDzzruWzF6vWd2hdGz8La9ZWw6+//DLX1DV3dFQaD0cFgQslg9HLc/sBzXd0FRg9FJBKFhUtXdnU3GAxGJ4B9KBkMRlpA3zw0b6Kv3gF77Qhv/et2WDTzJfj5k2fh/psvgUED+rpuV1ZSBDPOOQE+eeU+WPTVS/DbZ/+G5x+8HnabtnXCukccPF3sAz9333EbeOmRG8X6qnm+uKgA/nrJKTDr3cdh8dcvw6ev3g+nHXcIjBg6MMFf776bLha/7TBlgmvf9p++o1h+w2Wnpzx+tW/Td5kKrz95Kyyc+SL88ulz8NDfL4NNRgxO2Ab7gttg3/501IHwvxfuEecAj4uA2939twvgu/eegKXfvgLfv/eE+O7WHqJ/3zK4/ZpzYPYHT4m23n/+bvi/g/b07PfXbz8i/qW6pjo2GzUM7rj2XLHtkm9egTkfPg2vPnYznPB/+znOB2LHqRPF3/SP/DiT+VAO6N8Hbpxxhmgfj/unD/8Fj9w+AyaOH5303OO+8PzN/+J5mPf58/DUvVfDZpsM8zx+BoPROWCFksFgZIQ/HnEA7LPbdvDeJ9/AV9/Nha0njIVD9t0Vthi7Cex95LkQCkfsdYcOLoeXH7lJECpc96Mvv4eC/FzYa5dt4Zl/XguXXv9PePaV9xL2ccBeO8EeO24DH33xHTz90jswbPAA8XtuThBefOgG2GqLzeCnXxfBq29/DMVFhXDuKUfA9ttsmdDOky++A7/fbzc47vDfif3rOP4P+4rPp158J+3j33/PabDHTlPgnY++Er6DW47bFA7ceyfYcduJcMgfL4VFy1YlbPO3S0+D7bbZAj74bBZ8+Pl3EI3FxO+TthwDzz/wNygqzBfnc/7i5YLIHX7A7vC73beHI8+4Cmb/vMBup29ZiSCyo4YPhq+//xm++eEXGFDeF26+4kz4dOYP0F5AwvzQrZdBTk5AXLP/vPMplBQXwpbjNoEzTzxcnK+f5y0W7hIXnXEMrFi9Dl54/QN7ezwvyTB8yED4zxO3wOAB/eCzr2eL9ocM6g8H7r0zTN9lWzj1opvgf599m7Ad3jd4Xqz74r8wZtPh4rfJW46B3Q87C6qqa9vtHDAYjMzAhJLB6OXwigpuaQnDPx5/KeF3JHr7H3sh/LZwmf3bP2+6GA7dbzf43R47wBvvfW7/jkrbsMHl8Oe/3AqvvfuZ/TuSk5cfuVEQrfc+/gY2VFU79jF95ylw3Nl/hY+//N7x+5//eJggk/955xM4c8Zt9u/3PPICvPvcXQl9RdKF/UQlsk/pQ7Cxps5ehiR3l+0nwbc//gLzFi2HdLHP7tvDCedc5yA8Jx9zkDiWGy//Mxx5+pUJ20wYPxr2OfJ8QbxU3PO3C8S5OOvy2+DVtz+xfz94n53hgVv/AvdefyHsdtiZYJqm+P2yc44XZPKhf70G194WVx0f//eb8MaTf4f2AJLWf954MfgDPvi/065MIOJIAhE/z1si/lmEcn1GrhO3XHmmaOfmfzwtrh3hyRfehlcevRnu+tv5sN1+J0NjU7Nju3332AGOOfNq+PybOfZvqH6fc/L/wVG/3wvue+KVNhw5g8FoC9jkzWD0ciAhcPt31p8Od13/0efecJBJxDMvvys+t95yrP3bFmNHCfPkWx986SCTiNq6Brjt/mchPy9XmM91vPvx1wlkEoGm3Wg0Cjfe+5Tj99XrNsDDz77u2t+nXnwb8nJzhLlUxbGH/Q58Pp9QujIBKmq6evb4v9+CJctXC4KKqqyO+554OYFMbjt5vFDYZs3+1UEmEa+/97kgw2jK3W7rLcRvgYAfDtt/d6irb0wIpJrzy0J45R1nG60FnmMkuahCuqm6a9ZXtql9JJLozrBy9XpxXlTMmv0b/Oe/nwpSu//0aQnbvvbupw4yifiXvPcmK/ceg8HofLBCyWD0cgyZfFBG6yN50YGEDlFaUmj/NmWrzcVnSVGhqwrar0+p+Bzj4v/2w9z5Cb+hWXiTEUNg1ZoKQUZ0oPnXDS++8RFcfu4fhdn7waf/Y5MzJJioWKqKajpwI1mxWAy++fFX0b+Jm48WfVTxo8vx4HoInSARvvh2jjDjT9h8U4tcjhoGBfl5Yv9IKnXMnPUTHKmR5tZgm63GiU80zXcE8HgQX//wswja0fHFt7PhDwfuARM2Hw0vvfmRY9ls13vPOtelJUUd0l8Gg5EemFAyGIyMUFNXn/BbJGoRA5/fb//Wp6xEfGLwjVsADqGwID/ht4rKjQm/FRcWWMs08zhhQ6X77w2NTfDyWx/DH4/YXyim6N+3z27bw8DyvsJ03BIKQyao8NhPxYaNdtCQjvUbEreh9dZvqHJtb12F9XtpcaFNzJMd/3q5/7aC9ocpfzoC6POarL/rKjY6+qEr2zqiUcsf1e9ngxuD0ZVgQslgMDoEdXLyv+qWh4SZPBNIl0Fnew2WKlfet8x1m/793H9HoPkWCSUG4SChpGCcf72cmblb7N9jP+X9+1j9dFEPTUg8IFqvvJ+1nQ4kvIhauR7lcvQ6foyadkMsZkIw6D7Uo2lbR428boMG9EtwbWgP1NFxeB639TvnrmQwsgv8SsdgMDoE3/00T3xidHN7oL6hCZauWCPSE2E6Gh3ka+iGXxcsFSbxffecJqLS0dcRKwAtXJJ5jkS3FEToi7nd5PHi759+W5RWO3N/Wyw+UTV1A/2O0ewIzOeIQSoYVe6mgk7zaKemtl6QUDTz65i0xZiE376fY123PXeektZxoE+r35f+VELHjdfLTVXccepWjuNmMBjZASaUDAajQ4C+lujvh2l2jjpkL9d1Nt9spO1LmQ5eevND8Pv9cPk5Jzh+HzKwP5x6zMFJt33yxbdF2qGHb58hg3HSTxWkAskopqpRcdJRBwj/yc+/mZ3gP+mFb378RRBa9JPUA5PwOxLXRUtX2r6h6G/4ikiTVCCCplRg5Pth++3muh/0R0WF8kjtGqAPqRsJf/GND4VpGfNNuqVioihvAvqhYsqfdIFBPZ/M/EFE2Z967CGOZUj2MVsAtvnOh1+l3SaDweh6sMmbwejl8EobhPjvR1+J1DCtxVkzboMXHr4B7vjreSK1zvc/zYfaunoYPLA/jB8zSvw78PiLoXJjTVrtYVoYTB2DuSVHjxomiAkSrIP22VkEruy35zQwZY5HHW++9wX89eJTBPmsrKqBtz/4slXH9N7HX8Ojd1wu8lAuXbFaKIbTd54qciBefuMDGbV13lV3wr8f+Bs8cMulIrIdVcjRI4fBvntsL0zi5155p50yCHHzvU/DzttNEoncJ22xmZ2HEtMMffj5LJG2Scdj/35TkMmbL/8z7LLdJFi9doPIJzll0ubw/iffwN67bedYH48D0xhhsvaXHr4BPvzie/h1wRLhw4rXa8igctjhgFPs9T//era4Hk/efZVQZ8PhCHz1/c/ienjhL9f/E1574la4+sI/Cf/a2b8sgCEDy0U+z5gZgwuvuVv4vjIYjOwBE0oGo5dDV7tUYH7BthBKVKP2PfoC+NPRB8IB03eEw/bfTaiDGNiCSbyR7KA5Ol00t4TgD6deAZf8+Vih4p163CGwYtU6uPfRF0XUMBJK8rXUEY5E4JW3PxFk7IU3PnAkYM8Eb384U6SqwWTqe+0yVbT71v++hJvueRIWL1+dUVuoHmJOz/NOPVIon3vvup0gdJg6566Hnk9Iko7LDjnxUpF7EddFZXLxslUw48b7RVoiN0K5YPEKOOr0q0QOS9wGA6jwXB10wiUiNY9OKBGYgH2/Yy+Es048HHbefhLsNm2yMJ0vXLIK7n3sRce6V936sPAQ3Xm7rYSZHBVkTGuUjFAuX7UO9jv2AjjvlCMFGcdKPfX1TSJV1N2PvOBI5s5gMLIDBgyY4uL+zmAwGNmFYw7bB267+hy49G//9Ay2wZJ9O2yzJezy+zNgyfI1GbWPJuK7rjsfzr/6LkdVGAaDwWCwDyWDwcgyUPSziqGDyuGCU48S5tb3P/3GdbvJE8aIQJePv/whYzLJYDAYjORgkzeDwcgqPHzbDAgG/DDn10XCHxPrQu+167Yi6feNdz9p528kYHAJpsBBP0KMSL7tgWe6rO8MBoPRU8GEksFgZBVefusjOPyAPYRPJgbkNDQ1w/c/zRPlD9/5cGbC+meddDgMHtAflq1aK4JcfpzL/nkMBoPR3mAfSgaDwWAwGAxGm8A+lAwGg8FgMBiMNoEJJYPBYDAYDAajTWBCyWAwGAwGg8Ho+UE5Zfn5UNfcDFGlYkQm8BsGFOflcRtKG5uPGgyGz4SYSEmcOXxgQH4wB5rCoR7Rhhkz4Lela7r8uvSENrpDH7gNbiMb2ugOfeA2uI1U26e7XVYolH0KCsDva31XcVtuw9lGeUkhxEysD2y26h9umxcM9pg28Hx0h+vSE9roDn3gNriNbGijO/SB2+A2kiGT7bKCUDIYDAaDwWAwui+YUDIYDAaDwWAw2gQmlAwGg8FgMBiMNoEJJYPBYDAYDAajTWBCyWAwGAwGg8Ho+WmDGAwGg8FgdD1GDh0Ih+63C/gMw5GozQCA3GAAWsKRViZw4za6og3DMGDF6vXw4psfQ1vBhJLBYDAYDEZaZPLIQ/aEfz7+KjQ0NScQl6DfD+FotE3kh9vo/DYO228X2H7r8fD1D79CW8AmbwaDwWAwGCmByqQbmWRkN1577wvYaeqENrfDhJLBYDAYDBfsV2bC8eWxru5GtwGauZlM9jxEo+1zj7PJm8FgMBgMF7wx3ppon67o6p50D7TW7MroHdeWFUoGg8FgMBgMRpvAhJLBYDAYDAYjDXz99iNwyrEHd3U3uiXY5M1gMBgMBqPH4qVHboSf5y2Ga/7+SJvb2u/YC6GpqaVd+tXTwISSwWAwGAxGr4bf70srOKVqY22n9CcbwSZvBoPBYDAYPRJ3Xnc+7Dh1Ipx67CGw+sc3xL8jDp4uPvfYaQr899k7Yem3r8B2W28BI4cNgsfvvAJ+/OAp+Pmz5+CtZ+6AXbaflNTkje0cc+g+8Ogdl8OimS/B568/CPvsth30RjChZDAYDAaD0SNx9a0PwazZv8K/Xv4vTJp+vPi3eq0Vtn/5uX+EG+95EnY79Ez4df5SKCzIgw8+/w6OPO1KOOCYC+HjL76DJ+6+CoYOKk+6jwtPPwreeO9zmH7EOfDh57PgHzdeBGUlRdDbwCZvBoPBYDA0PLkZ559MG4WlYBaVQczvBzMabVPqmpRt1FcDNNSk3WZdfSOEwhFoam6Bispq8dtmmwwTn7fd/wx8+tWP9rrVtfXwy/yldnWZv9/3DOy75zShOD7+/Fue+3j+9Q/gP//9VPx90z1PwSnHHAyTJ4yFL76eDb0JTCgZDAaDwdBwbDlnXUwbW+8JsMuhEGmHplK28dmrAJ+/2g57Apj9ywLH94L8PLj4jGNg+i5TYWB5X+FXmZebA0MHJ1cof12w1P4biWttXQP071sKvQ1MKBkMBoPBYLQeP3wIsOB7CPj9EGmDQolI2QYqlO2ERi1a++oL/wS77jAZ/nbHY7By9Xqob2yCh267DILB5FQpEnH21wQTfL7e51HIhJLBYDAYDEbr0VADRkMN+Px+MKLRVlddQVNzW9twQzgcAX8aBG/byePhhdc/gP9+9JUweQdzgjBsyIB27EnPRkaEEqObhg8ZmPD7E8+/BZff9ADk5gThmotOhoN/t4v4++Mvf4AZN94PG6ribxTo3HrTFX+GnaZuBQ1NTfDiGx8Kp9j2qiXJYDAYDAaDQVixeh1sPXGcIIeNjc3gM9zJ5ZLlq2H/6dPgf59+A37DBxeccbTnuoxE+DJN6ElRUvjvyNOvFL+/8f7n4vPai0+BvXfdDk6/5BY47OQZwgfh0TtmxHfm88FT914NOcEAHHziJXDeVXfBEQdNh0vOPDaTbjAYDAaDwWCkhQeefFWIVp+8fB/M/fgZT5/Ia29/VATmvPbE3+GRu66Aj2d+Dz/9tqjT+9srFEo9oefZf/qDYPQzZ82F4qICOPrQveGsGbfBF9/OEcsvvOZu+PQ/98M2E8fB9z/Ng92mbQ1jNx0OR55+lVAtf563BG69719wxXknwu33PwfhSHu49DIYDAaD0TZ8Vw8wpQigiqelrMfi5avh4D9e4vgNTds60G/yiNOutKO8w9EoPPH82451tt//FMf3IZMPSmhn/C5H2230JrTahzIYCMDh++8BD/7rP+L7VuM3g5xgED5TwuQXLl0pLtCUSZsLQjl1q83ht4XLHCZwNIvfcuVZMG70CJg7b7H3/tpwYWhbbsPZRqANTsO0bU9qo7tcl2xvozv0gdvgNtreRkyGVwDkeKzT254VQ/5zXWYY8U+zdR6Q3EbXtWF43Od4T4TSDLRqNaHcd88doKS40Gb5A/r3gZZQWITLq6ioqoYB/crE3+X9y+w8UAQil+X9+wDM897fgOLi1naV2/BAaX4+t9ENr0tPaaM79IHb4DZa20ZuoEoksQkaBgwtK+vQfnT3c0HIDQZSks62vNxzG13XBl5br/t8SWVlevtoVc8A4Ojf7w0fffEdrKvAh67jsb6uTsjPrQE+APigcBvxNkZCX6hpaoJILNbqmxNJXE9po29hQbe4Lj2hje7QB26D22hrG9Gh1m8GmLCq2j1VTW97VlrCEc/lqIDhWIrjsNkGNY3b6Jo28Nq63eeZKN+tIpTo0Ir1LU+56Cb7t/UbNorIblQtVZWyvG8ZrJeqZMWGath6wlhHW/37Woy4YsPGpPvEmzhd2ZXbSA94g0XaGF3fk9roLtelp7TRHfrAbXAbrW/DmnxxOk21j97yrOAZ8aQkkqwgaWl1yh9uo8vawGVtvX9apaMedchesKGqBv732bf2b3N+XQihcBh23i5eSH30yKEiTP+72b+J77Pm/AabbzYS+vWJZ5DfddpkQUDnL17epgNhMBgMBqO94DMAoqb1yWAwOkChRPn0yIP3Evkj1dyRWC/zuVffh2svOhmqa+qgrqERbrjsdFGUHQNyEJ/M/AHmL14B995wIVx/1+NQ3q8P/OWs4+CJF94StTYZDAaDwegOQLUlbFoKJYPB6ABCiWWJUHX893/eT1h27W2PCFn14dtnyMTm34vE5oRYLAYnnHsd3HzFmfDGk7dBY1OzIKZYgJ3BYDAYjO5GKHM4rzWD0TGEElVGt7xLCIzyxoo5+M8Lq9ZUwPFn/zXT3TIYDAaD0WlAU3fENnmjhxnbvhmMZOB3LwaDwWAwPBRKBJu9GYzUYELJYDAYDIYGVCZtQsniJIOREkwoGQwGg8FwUyhl3ClHemc3XnrkRvjrJc6SiW3BndedD4/deUW7tddTwISSwWAwGIxkCmVXd4bByAK0ulIOg8FgMBi9woeSFcqsBaqJO06dKP6deuwh4rft9j8ZCvPz4KoL/gTbb7OFyDjzycwfRaaaqupasc5+06fBuaceCaOGD4am5hb4+bfFcOL518OZJx4GRx48Xayz+sc3xOfhp8yAmbPmQm8HE0oGg8FgMDSwD2XPwNW3PgSjRw6B3xYus1MURiJRePtft8Ozr74nSGRebg5ccf6J8MCtl8IRp10JA/r3gXtuvAhuuOsJePvDmVBUkA/bb7OlyMN9/5OvwphNhkNRYQFccM1dor3qmvouPsruASaUDAaDwWC4KJSYNgjBJu/kGBQ0YUgOQMAXg0is9WUCkbenamNNCGBtOH2Gj0VXsHAKqowVsgz0eaccAXN/Www33/u0vd6F19wN3733BGw6YggUFuRDMBCAtz/4ElauqRDLkZASmlpCkJMTtNtjWGBCyWAwGAxGMkLJCmVSnDbQhKuH48mKV89rPZK3cd0KA65b2bYLssW4TWDHbSfCgi9fSFg2cvhg+HTmD/D517Phgxf/AR/P/F7k337r/S+gpq6hTfvt6WBCyWAwGAxGEpM3R68mx0PrDHhzowEBnw8isVgbFcrkbaBC2VYU5ufD+598Czfc/UTCsnUVVaKq33FnXgOTJo6F3aZtDX866kC47Ozj4YDjLoYVq9e1vQM9FEwoGQwGg8HQwEE56QNN0OvCAEG/D8LRtpm829qGG8LhCPh98deCn35bBAdM31GQw2g0URGlyz3rx1/h2x9/hTse/Dd8886jsN+eO8BD/3oNwuGwoz2GBT4jDAaDwWBo4KCcngMkjltPHAfDhgyAvmUl8MTzb0FZaRHcd/MlMGnLMTBy2CChRN751/PA5/PB1hPGwpkn/QG22mIzGDqoHPafPg369SmFBUtWyvbWw/gxo2D0yKGivUCAvWwRTCgZDAaDwdDApRd7Dh548lWhRH7y8n0w9+NnIBgMwCEnXipUxufuvw4+fPEfcN0lpwofSTR31zU0inRCT//jGvjstQfgL2cdB9fd/ih89MV3or1nXnkXFi1bBe88e4dob9vJ47v6ELsF2OTNYDA6D6MnASya3dW9YDBSghXKnoPFy1fDwX+8JOH3Uy66yXX9hUtWwh/PuQ7C0air6b1qYy0c/eerO6Cn2Q1WKBkMRuegfDjAERdZnwxGNwdHeTMYmYEJJYPB6BwEgtannw0jjGxRKC0myRMlg5Ea/JwwGIzOAUVFGiz3MLLEh1IGALNCyWCkBhNKBoPROTCYUDKyBxyUw2BkBiaUDAajc+CT0zITSkYWgINyGIzMwISSwWB0DuxEwDw7M7o/kEQyoWQw0gcTSgaD0TlgH0pG1sBiknaUd9d2hsHICjChZDAYnQM2eTOybGIkQonmbwaDkRxMKBkMRicH5fCww+jeIALJJm8GI33wyM5gMDoHbPJmZNnEyFHevQOrf3wD9t1jhx67v84CZxhmMLoD+g+F6MARAGvnQ48Fm7wZWQJWKDPDyCF9oTA/BwKGHyJmtE1tpWqjoSkEy1ZXZdRm3z4lcMmfj4W9dtkW+vcrg5raevhl/hK486F/w7c//grtgYvOOFqQxL2PPA96K5hQMhjdAafeBGIIfegC6PkKJRtGGFmmULoQylVTonDVSoCPIp3atW4JJJNRdDj1xyAaNV3rX6cDcZpTtIH7yhSP3DYDgsEAnHfVnbBs1Voo71cGO283CfqUFreypww38MjOYDA62YeyqzvCYKRJKKlSjss6A3MArh7aNjWO0fEoKS6EHaZMgBvufhK+nPUTrFpTAT/OXQD/eOwleO+Tb+z1+paVwKN3XA6LZr4En7/+IOy167b2siMOng6/fvaco11UI9F0TcsvOuMY2HLcpuI3/Ie/ITYZMRheefQmWPz1y/Dxy/+EXXeYnNDHzTcbCS88dD0s+uolmPvxM3DrVWdBQX6eWDZ29AhY8f1rQmVFlJUUwcrvX4P7b77E3v68U46A/zx+i/h72tQJYv87b7cVvPPMHbBw5kvw8mM3w+iRQ6GjwYSSwWB0DtjkzchSk7dXlHdrlThG56GhsQnqGxoFAcwJehtlLzz9KHjjvc9h+hHnwAefz4K7rr9QkLd08Pq7n8EDT74Kvy1cBpOmHy/+4W+GYcDDt18O4XAEDjz+IvjLDffBFeed6Ng2Py8Xnr3vr1BT2wD7H3shnH7JLbDL9pPhhhlniOXzFy2HjdV1MG3KBPF9+222FN+RJBOQRCJZVvGXs4+Hv97xGOx37AUQiUbh9r+eCx0NJpQMBqNzwCZvRramDfJYjwll90c0GoPzr74b/u+gPeHXz/4Nrz1xC1x2zvEwfswox3rPv/4B/Oe/n8LSFWvg5nuegqLCfJg8YWxa+2huCUFDUxNEo1GoqKwW//C3nbefBJuNGgbnXnUn/DJ/KXz9/c9w071PObY9dP/dIDc3B8698g6Yt2g5fPHtHLji5gfgDwfsDv37lol1vvr+Z9hx6kTx97SpE+H51/8HOTlB0XYg4Iepk8bDV9/NdbR7yz+eFr8tWLwC7n/iFdh28haQmxOEjgSP7AwGo3NgE0lWKBk9IyiHCWV24O0PvoRt9v4jnHT+9fDRF98Lcvbuc3fZZmnErwuW2n83NbdAbX0D9O9b2qb9brbJMFi9bgOsq4gHEX035zfHOmM2GS4ChHCfBAwU8vv9MHqUZaZGYohEEoFK5effzBHkFJXJyVuOEaRSDy76RTmeig3W/omgdhSYUDIYjNYBTdfB3PTXZ5M3I0tAEyN5SBoeVJIJZfagJRSGT7/6Ee56+Hk4+I+XwguvfwAXn3GMvTwS0fxhTTSqWHdCLBYDQ7sLkMR1FmbO+gnGbjpc+GOO2XQ4fPPDL8LEjcQYTd9zflnoIKT68ZjyRjU6OEM/E0oGg9E6TD8G4OKH01+fTd6MLAHNu2Ty1qdhzkuZ/Zi/eLkd+JIKlRtrhQkc/R0JGICjIhSO2ASUsHDJShgysD8M6N/H/m2bieMc6yxYsgK2GLuJo+1tJ48X5vNFS1fZ6ml1bT2cd+qR8PO8xdDY1CxIJpJJJJW6/2RXgUd2BoPROoyd2soob1YoGVmiUNpBOU4tkkzgpPwwui8wNRBGUB+2/+7Cb3L4kIFw4N47wZknHg7vfvxVWm388NM8oQDOOPcEGDlsEBy6324Oczli5er1MGLoQNhy3CYiYhwDgD7/ejYsXr4a7v7bBbDF2FGw3dZbwGVnH+/Y7tW3P4GWlpBYZ9zoEYIgXv+X0+Gltz6GDVXV9npo4j5sv91h5izLVxJ9MtGPEtMf0W9dDSaUDAajdciUF9om747oDIPREQql4a5QEqHs5H51V2CycX/AgIDPZ3228l86beC+MupbYxP88NN8OO24Q+CVx26Cj17+B1x65nHwzCvvwhU3P5hWG6gOnnPFHbDnzlPhwxf/Ab/fd1e4/YFnHeu89b8vhH/miw/fKFL//H6/3cA0TTjlghsgLzcH3vrXHXD7NefAzf942rEdEtVjzrwGykqL4O1n7oCHbrsMPv9mNlxx0wOO9WZ+N1eY2UmNxLaRZOJneyVnbys4sTmD0dtQ3AfgkDMBnr8NIOz0u8kImSqNbPJmZKkPpe56RiZvJpQWsHINnqKg3w/haLRNic3b2oYONEVjZLUeXa1iyOSDEn7bavdjRT8I//3oK/FPxbOvvOfYz2mX3JxwLKhQHvqny5LuD9MNHXHalQl9UG+7R555XfxT8acLbkjYBtVKvX0M+hk6+aAOv195ZGcwehu23hNg+DiAoZu1saHWEkqWKBnZZfJmhZLBSA0mlAwGo5MUSo7yZmQHSJFkQslg9EZCOXVvy5THYDC6Jzgoh5GtQTngYfKWy4flMLVkMDImlIMG9IV7b7hQOJ1i3ckPXrwXttrCaTq75M/Hwg/vPymWP//A30TuJBVYzugfN14E8z5/XtTHREfVdMP33WEA7H08wEFWqSIGg5EM7UToMvWFZB9KRramDTK8Fcotc8Mwf3IY9i9jUsno3choZC8tLoTXnrhVJMw87uxrYffDzoLr7ngMamrr7XXOOvFw+NMxB8JlN9wHBx5/sciX9Ox91zlK/vzjxotFePxRZ1wFfzznb7D9lAnw96vPbv1R+APOTwaDkRptzXlCk2wqxZGeSzJ5c5g3I9uCcsCbUA4LWmuNy+/5hJKf3J4Lo7MJ5Vkn/QFWr90AF1xzN/w4dwGsWL0OPpn5AyxbudZe55RjD4a7H34B3v34a5GME2tYDizvKwqzUymiPXeeAhf99V74Ye58+ObHX+DKmx+EQ363i1ivVfDLiYqTgjEYAtEJOwEcf1XnDEGpFMdLHwPY8eA48WSTN6MHJjbvDXd1zDShsE3WREZ3hN/fPlajjFrZZ7ftYPYvC+HBv/8F5nz4NLz377vgmMP2sZdjUk8khZ99/aP9W119o8gBNWXS5uL71K02FzmdsFQQAdePxUzYOs1C7IlHQYQy1rrtGYwehui+fwIYNsZ9oT3ztVWhTIMgBnOsz7FTOCiH0fko6Qdw3j8BCkvbmNjcW6HsTTLGq+98BmeddCiTyh6GQ/bZCb5oh+ToGdmIRwwbBCf8337w0L/+A/c+8iJMmjAG/nbpaRAOR+DFNz60ywtVVMazu4vvVdUwoJ+1rLx/H6hUsr8jotEYVNfWOcoT6cB8Tl4wc3IgLOZJU6xnggGxaQeC77v/gRFqsrdN1kYq9MQ2MIFsa0Hb9qQ2uvK6qKl626Mf5K+Y49JWxPBBTB63z2V5uscSksQwGAiKZ89tezO/xHo2Y1Ew/AGxX7/fL/5l07PCbWRnG9FxUyFaUAz+TSeA/5ev0m4j1493agz8Ph/EzBgEfT7Hs5Tnx/sd14kzTVzX7Xlrj+PoLm2sWbsBXn7jYzjt2ANFmUFMqk3wGQYEA34IR6JCyWwNuI3ObwOXr1xTAT/Mme96/+I9EVLycbYbofT5DKEs3nyvlel97rzFsPnokXD8H/YThLIjMaC42HNZpLAMVohBwA+Dy8qgecBIWLPLYVBUVAx9v307rTbaox/Z1kZpfj630U2uyxL5abZTPwhDy8oSfqvKy4MaAOhfWAT5LssJqfqxTBLTIWVl4IuEXLcP9RkEWI021wAI5OUBeluXFRRCSZL9ZtIHboPbSIaaggKoAoC++QVQ5HHPubUxKAdfgzZCv6JiMGEj9C0ogKFl8TFmSDCCT5IgkYSy/Dw4aFAQFoUCUBPz9cjziYg1huA/r37U5n0xuhfc5grCksrK9ieU6ys2wvxFSN2chc3332tHa/mGjeKzvF+Z/bf43rcMfp6/WPxdsWEj9OtblmC/LyspdmyTsO+6OkfWehUmWAE/LaEQrKquhli/keJ7fX0dNFVXC4aND0qyNlKhp7UxEvpCTVMTRGKtcxNAdQtJXE9po29hQZdfFwHDgPW1tW3uBwGfBx2RFqs6zob6OvC5LE/3WGJSlVxdWwtGqNl1+5aicvFbS0uzqCSBqG5qgjqX/bamD9wGt5GsjWhTk/isaqiHGu2eS9ZG/wJrLFlXVyfu8prGRlhVHa8qVZJvLQ8rY05NUzM8P6IBZtYZMP3XYLseB7fBbYS7qI1MlO+MCOW3s3+F0aOGOn7bdORQWLVmvfh7+ap1sK6iShQr/3mepbkUFebD1hPHwlMvWkrhrDm/ibRBE8ePhp9+XSR+w/VR/cQgHS/gifCUXWW9VdOMWevkWP4d0aZ6iCrbJG0jTfSkNpCARaJt8zvtSW10j+titEs/CK7tSLOHIOBJ9pO6H9ZzF46Zru3g9pGgpeqYkTCY0kSOa6rPZfe/JtxG1rYhLXzRWMzznnNrI4r3NL4IRWMgbm8xt8SXo8+/+FQsiGgap2jvTI8ra84nt9Gr20iFjHT5h/71GmwzcRycc/L/wajhg+HQ/XaD4w7/HTz+/Fv2Olhr8rxTjxQBPJtvNhLuuf5CQTKpBubCJSvhw8+/g9uuPgcmTxgD204eD9dfdjq89u5nYr1WgdKSkH9AbqH12dzYuvYYjK5CZwastFdWhGR9zpfPYjTCpRcZnQ+jdfc6TYxIEc1kic1dtu0bANiqoDeF6jAYrVAoZ/+8AE6+8EaYce4JcMFpR8GKVevg6r8/DK++/Ym9zj+feFkkKb/1qrOhpLgQvv3hFzj2zGugJYQ+KRbOvvw2uGHGGfDCg9eLN723P/gSrrzlIWg19LRBeQXWZ6xj2TiD0d4wsynpdzpR3nmF8WeUns9sOkZGT2GUGW1FUd1WaI53YnNsFoNA9T18PykGgZmtD5JhMLIRGWcC/99n34p/yfD3+58R/7yAaYPOmnEbtBsoHQn5s9AkxhMXI9vQGepde+0jLUIpX+6CufHnk8HobGQoGNoKJRJG0zuxuQrW3Rm9HT2Dcdkm75hzEtOThzEY3R1ZZQ5OI7F5MC9OKNnkzehsGO2kUKZh8ua7mtHb0TMIpZ3YXD7eMiiHFUpGtoECV7pFhZs0m0lKEAPBeIJzO7E5P5eMLFIoUyU2N71VSwajN6FnjOx6UA5NWDxxMbINnXnPpkteUV10byB1n21CyQolIzsVSpxWEhRKhVASAnxbM3o5egbj0ksv0iDShuopDEbXoDN8KOnTSK903cUPW6UTW+NDSYQykKO86PHMy+gk0L3W2ihv0yKV6UR5M6Fk9Hb0TIWyNaa1LXYAGDC8AzrHYGSAziRb6TwfxbIc6vBxrSOUflWh5FrejM5G6+41PW2QV5S3CNgxrHlHjemOcNYgRi9EVhDKaG4hRKfsnUbaoDYolIecCXDyDW3pJoORJT6UErSvojKAaQe5r0OJcF2rJWRi8kYfSnZFYWRJHkpDUShTmLx9LgpliBMaMHohsmJkr9zx9xCdfgxAQUl6QTns/M/IVnRqUI783PckgN3/DyBXZkdQEbPKJYLhb1tQDloRWKFkdDpa6UOZQWJzV0LJCiWjFyI7GBdNRDQ5ZRKUM3orCF36OMQ8AwsYjG6ErlAobfXRZRakn9wUynR8IvGZJcsBmb85wQqjmz9PqdIG0XJTUSvVSHAmlIzeiOwglFTxhoilDvqdTGrq5+bbiT8jBaWZ7zc3H6CwNJ6GiMHocHRiYnNbwU+yT/tZSlL1I5klAElkS3Pc7K3un8HoNBhtS2zuVSlHrJvoQ8kmb0ZvRMaVcroCBhFKUiJ10O80sam+WlSdozUR3xc+aH021AL887zMt2cw2sOHEsncqC0AFv+UeYPYnpf/mE0s7R9c9u1L/uyp7aAVAM3mTbVOhTLUbBUbIAsDE0pGZyGdwLE2Jjanddnkzejt8GUVofQyees+k6qvljS3talGcqGH7yaD0d5wu0+n7gNw5CUA5cPapz17mTZNur102eq/P3U7x10JcM7dzmWCUDbJv1mhZHQ2WpfE30iZ2NxijPiu5ndRLZlQMnojsoNQUqRpKh9KeupVpVIP1GEwujPcyFaO9P8t6dtB+9I/1XVIoUyDUA4a6WHy1gllVgw7jJ6ATHKueiU2hxRR3m4KJZu8OwUBw4QiH7P37oLsGNkp0tSTUPqTmLwtMmomNdllx2lg9AK4TXyNddZnfnEr2vOl4UPZVoUyRdogNHmrxJgVSkanoXVFLhyJzdGHMo0o71xWKDsdd44yoXr7mCCWjK5HVjApg/wgSeFIFZSjEku5relFRlOpL2Jjft1kdA5MN5WwpbENhNJIX6F09d+kZ6mVL2QBRaFMp08MRnfwoUw3sbkSlJOjKGVh5jedguml1ok+UNZfYHQtsoNQRiPJCaVt8tbUFBwFiFDaKUtckMocXrUu0y4zGK2D68QnfysoakV7GezLjRjSs5GOyTuVQplWpxiMDkDGJm8zvcTmZvzvHGUlJpSdgxZ5nrcv4hPeHZBdaYPSDspRlEqpLsaSKpQe6gtui5MhK5SMzkIylbC9TN76vpL5mWUS5S1BQ7sIhMNnk4JyPNbvccB0Y9vv39W9YAi0j0LpZfLGZmkZEcql+vsTo0NggAmbyYx+m+czoewOyApCaRCh81IodZ8wh8k7DR9KN4US28B/aK5Lti2D0Z5wm/jofnarZNOmfaXhQ6m/pKUVLa4VIuhtJm8sY7nnUQADXYKUGJ0LL3/htqYNopoAqg+l/GNj1JmTktEx6BcAyPcBLGoGGJ/G0Ih+liNymHhCbyeU8Tx3HiqjPelpDtjKIJLch9KFMAbkb6hQJjOXMxidkYeytUQsWVCOHt2dbN+ZBOXQs0afusm7pwfBkc93XmFX94SRcK+3IrG5a9og63OHYhOmFoQcCmU4lrg+o31w1qAYRKZF4dxBMciRF+m3JoCRHlqTimuGmbB4SgyCHMDTYciKkd3OIelF7PS3ULVSjpwIk/pQuvmHEclEc10yMspgtCvc/BjTUAnbFJRD35PtOwMfSnp2qNxpc2P6ffrdiQBb7ABZDTLxJ1OU+w+NVw5idDzakjbIzYdS+XufIkkoffEIb1YoOwbXDrfI4B2bmDBWmrvrogYE0aCYol77OGkWH86PXe8mlPZE5zUAGx7KJH7KyS15UE7A+7d0TN442coSjwxGm5A00rqdCGWCi0g6QTnp+1DazxyVLG2uT90nwqYTAQZtAlkNisrP9SrZagCcehPAAad2Zq96J3Q3qNakDUqiUKoghRIJJSuUHYM+gcRr1BhLDIpyw8qQtcImXEm5dxNK2wyYyocyIcobCaVUKMmEna5CqZrrUimU2/4O4NCzAQZn+UTI6J4mb0MLOkvVhnPjJJOskT6ZzUTppOeFFMqmhtT7UbdtDXHuShSVAZx/H8Dm2wJM3AUgEk6uUFKC+qGbdV4feyvSuX/bkNjclVCiyTvDbvYPmLBHCZti3XDJkBicPCAxMJZ8VhtlzC4pxF5YawnJMDKXz3NHITuiTWgC9CJ2+luoo1IOpGHyDniTTKlQuuYHJOQXOSdQBqMrFUqVeCZLQ6TX8Hb1t6TflHaK+zhN4Pp2+KxFwwCkUDbpCmWS48Btsy1oZ9hYaww49Bzr+1uPxKO93VA2IHl7m022MkssmtPOHe2FaGUeyvjdbSRNbK7CYfLO8BZ+bVwEti40ITCTjeU6bhppTeKPrnf+XiDPd1OaCiVhE56mOwzZIQX4MiSUqulbmq7TzkNpq52KD6XYdzrcO8smQkb3gDrZJTM7k1KZAqZKPE+7BWD6MVp7vswr5agq/tl3A5x5h2ef7YwKOZJQNWsKZTIEspBQUiUj/ZzterilXuroIwllST93lfL/LgQ44mKArXYFyGvnyP7ehjYolFESIzJVKFtBKEexapYGnOeowG99b4g5FUsvUGnM/hwS0bsJpW0G9AoMsJfrpm/V5J2mQknE0055IiNUe0KkNypGU/eG8OEXdHVPGJkoirZCmeYspT4n+YUA2+2bXLVJpuK0Ig9l3IcyN3OFEv2ksy0KXM9TqxLzQaMS11drsk/e3bvdA05pXT5LdMEZt23m2/VEZOguQsC1UZlEiKubiQ9lzMg4KCfLXqHaDViH++3xURiaRjoftbSlqlDaJu8UJzEol/cNMHnvKPh6hGO1V5S3yDrrzywPJSmRpMhkolB2d9+v3Y8A2Pt4MEdv1dU9YXjcN+5pgzINLEgxsnr6UKZRy9tNMfPyocQXGKxyFW5Jvj6BXtqyRaE88DSAEZs7x49IyPm9sDRxO7R+bFwHsGFV3N9Shepz2lDrvu/RkwAGDE/8vbQ/wF7HAhwmze89GOv3OA7Ch56bfKVWBrThuxu9JmCUt761L4XJG7c/oTwGt4xMryhGW+/4B4ZUwzH9JLPKIhzS14R9ygD+r59F8nYujsG4HFkZT8OmWjBNIRFKF5P31PwQlEoFU1co+2aHo19WopszoDSTK+uDhlvaoGRpT9wUSjXKW/3dDTjiJAsa6i7o7oS3t8JBoJIE5aQqEepm8k62P51ApqNQ9h3k3R7BrxDKhLKLSQgjEdFsUCixrxN3Bjj2cu2FNMf6jqmS6qstf1MduBwLLnhlkKha4ySobjjiIoCTb3Bvu5egYcwUMMdsnXwlNx/gdBVK+bdbYnNfGibvxzYz4aIh6alh8UeiderZ9KIQPDI6+wjlZJmqda18r3pvfATeHFXluu4gbQoukLd6osnbhMeGVsNR/WKuCqUaKc5oX2TByK2oNqkUSjGYGlraoDQIpbpM99e0FcpkJm8ilN3cLO6mhjCyyOTdTgql3U4rFMqAi0e72E5pS6r5ZjAvsUpOWoQyCxRKtQwmWTOI/KHZHs3gdRsBilwIJa6Pyc9RvXUjlHiu53wW/zsT9CJC2aE+lIrJ2y2xuatCqUR5Z3oVfNk0IbcjRkjfUVIb40gk1kXaSaVtGqKG4/znGVYFnUFBE64eFrPzU8ZN3u17DIw4suP+TWnyU4Nw1Mk5rlAmnYzVQV0PQpA+lElN5oTunKgY1SJlsmEvkm4Exz3bDibvVL6WmfhQ2kUFiFC6PAe4nfJ8mCkVSl/3VCiR/GGgTDooUAglZXf44Ln4caMCiYTSS6GMRi1C6ZYDF881vsiKKl1pzn6bTLACgNRrSFH2vRmtjPLWTd7pKJSYXBsRbkUeSkMzy/YW0PHqZNEtErtYM2EjaXSL8i6Vj8xfhsbg6uEmTCl0+r2yQtnLCaVdKcfrKVUVTHUyEibvQBomb2UZDeB6lHcyk3eqtEbtjJotd4HQpY+nXnHcVIBLHwMYsw3ARQ+5+1wxuh5qidCk5Q/TzUOZyuTtodq4RnkrZFYo/i73OLajEk07yjsv0X/Sbb/2dl2oUGKfz7kb4Kw7MyeUlB6IxgoilBiM5FZ+UaQzk4TSLQcujj2CcEbdFUc3wn3UpQDHXOa8hlz6sRX+x+5BOen4UBL0SjnplPrr9YRSO6EDgtY58yvSR7Hf3eRt+1DKNkp0JVN+J4US28n3saTSawllQuJyz+VGokKZlsk74E0OKco7WVCOXbu4cxTK6im/c1+Ax4g58QiTdrMmyoNOT5gEXYkLoxukDWoHhTLVtU1wIUniUqI+N/gsub00aQplPLF50J1QepnkSeHvinsTX7wygUooKT1SqCWuWAqTdtj9fNmE0cPkLUziUeufG+FUA6MoBy4C1VX1ejGh9H55ykShdHv3StKcMHkry8vSsH/btTtacesT6YpkEUcam2cKxZFOja5Q0jnL86Vj8nZGgevBOBQNrp7bh0abcGS/GMycmH1+p90ZWUIoU0yojryTmkJpK47JTN7apKl+pqNQ2oSycxTKmD1RaKMPpiA5/kqAgSOt75VrnAqK4xiYUHYbOMyebsnFM1MoUxNKbZI10iCzCHyW3AiQrlzSOvg7pdSJ0Wc0tQ9lNgSPFZQkEjwy7wtCGbV8ll19JH3WciSVrssDcrmHSVxNmN5viHoBnWMkpozq7bBzuKY/3qE6huZT24cyzShvgjB5K9/L0kkQAq0nlBSMQv3t/jDhl61j8K8xMft4SUWkFEBlMrUPmbVVhXLXudaPhVJl9FIoW2JxP80ROaZQKL+VGczKAyZcP8KEbYvQBJ41J67bI8tM3qmCchSfSZzA1LRByRRKlQja5kUyeZNCmYxQ5nRNlLc+GeEEhcBUJoimuuzx8ezNUF9okgblpBnlnSmhJEKSLLE5/e32YvX7swCOnRH/Lp8V8cwRkURyJD6TEEq77S4eltI5z6oySASP1Fhh8o5ZhNJt3LAVyCQKJZ4vL4VSLemI5V4d4xebvNuqUK6eGoPrRphOhVJbx+sOxWToqBQ6FMo0CGVbTN6kzKWXoKjrUS7Px6a58fNEJu9YEoWymNIyxax/NgmNOU3aRCgpMf0/NzVh8ZSY8HFFNfOlSuuafi+zc22nPMqMXkAobfuCZ5Q3DRr++MCB5iZHUE4yQql4ANN6OEkgmaTIzWTO8Xoy9M6CboanvmKFDeyvrm6ohJdN3t0HakBLa+tpq0hlGvcKVEjmv0n99HL96DPQuR71gwglZRhIR6Hs6ntTNWerQOWforvVMqs5OqGUCqWXydtII8qbTN6uCqUklOijiX1SXxTVaz9yi9TH2tORobuIT/HZU30o03lUiMTga33GJu82EMq8LFMoN5ePy9IWNSjHdJDjO0dFhVLsZvJGBRj9VAt0k7dULMnkTT6WhIDctiVmCFV3RYu1s5Nc6oQzeoNCmTJtkEIgcbDGyMeBI6w2khFKdUCm9TAhcUMNQCSSunRjJ/tQ2tAnI+o7Bt9gSTdd3VAmtywZe3oH3Ep/ui1vLx9KfZJNlpZLbUsolKnlFvtZwRdBMnkjuRKfkTSivDuRUA4Ykai64rM/ZS+AQZs4n5c//Q3gD+dZP4hckw3xl088LiLNQVWhjI8JIlOEOIeSMCYjlLaPpZtCKWfkytUAhSUA59/n3Bbxy1cAW+zQypPSe6O8VQJD3nWZmLyjktjhVWiOOc236XSzNQHIFN2cLd6A4/Kt87EiZDiivDG9D0XKI04faLqavJFMojk73yOxeYnLScRrEvSZQj3G64KphYj0/6EfbsszYnsgOwLoU0Z5++KqgU0oownJno1khJIGd9oefaSwRi9NhMnURww+SLVOO8Fx2+sTIU0+OJn1GZQ4WTm+s0LZbaBel3YxebdWoUwVlIM+lEFLCU/28qSm/4nJ5yeiEkovhTKnc30ocX8nXw/w9duJCuU+J1h/33qS+Ij84ULre3HfeB8xxyaalZHgkc8kKZSY2Fz4UMaf0fC5/wCoqQSoXp+cUNqEk3wsDYjsfwpUhRsB3n/WIpH4jKNCqZq/DeXc1Wxw+lr2VmSo7pPqlaBQyt/uGBWDGnRtTaZQammDVFLkhd6kUI5Xbks7KMeXWIt7bUgzeUvlkRRKMnm3mNax53gE5SBWhxSFEtf1xU3kiH4BgDWcprl3KJRJFRRaLsxDvrhvE/lsEZKavHOUijikUJZYZc/w9dRr4O8Kk7dbmUi7HwFrEqutBOg70L3PpBh1tVmRkT7R7+igHP13FY4gN4zyDlhkKRnsQDgXH8ruZPLGMoUIPVekRpZxejI3nWh9qa6IH1uLPA9I6kiRJB9K08WHEl94+w/RFMhkJu+IzNwwBmITdoKarfe2Xhb6DwXYuNY96IeuIfbNy+c1qxH3i09v9cwIpUr+VB9KIojnDjbhquHeibkiismbCEtHE0oy9WabQpmrqITFAUs11JHvYfJGhZLIf0SSxFyPtEHUDqqftG2eTih72mPSRciyoJwkaYOo5i3VziVlMdwCvm/eSW3yJkJJEyiqFGjyFm2lIJSdafJWJyh9shATVcSabNCnzc3/Sk7sWfIy2zuQtg+l9rj2HQww4ykrMENFpgplMrMg3VOin5KguKYCgnjqHLco77QUyk5ObL79ftZnfQ1AbRXAvFnOfhDUsYOOB4+RUoqRQkljDkV543efL1ExxvYoD6XbuORX8lDi30oAkInXuv8wgIqVVl8S3F6IUFJOTJcM0dmM6UcD/EXLwZuMLGboLuKmULoG5aRQKJHAEFlSVTbPbhrtEJTTjQd19IdEhXHbIhP2le9vuco5GpMXN2lTdDYSSCKZSBqJUIqgHFQofZQqyRC/WQqlCaXKI7WwGeDSpYZFKA1c3xDt4znDc70uFFcoGb2EUKas5Y0DCpqnSVlUTd7S9JQ8yjs3nh6ISBgS00ZJUr2iNe3tg51X9swtPYv6nSp0YP/dSLD0CWWTdxr43R+tAKduY/LW7n/pHwxDx2QY5a0o/g4fSQ+Td1gJTBNkR1P/VeBzFEjiQ5lMoWznxOZm38Gwfo/jwHS718sGWHlaEWg6xmNfvyLhxTB06s0QzZOErqkBgP4moo0EOsHkrfhQuhJUn7dCaWepwChvSTiVACATg3D6D7ZSguE+dHXbViibEoOHegIm7Jj4W7KX/VT+92kolLFMfSiTtJkKqmqWLkiZa0+F8oh+MZhU0H4MFSPnP5sQE36RBPRbRFI3s84i3RRtfcbqUmGiRgJJamZ1JE447aAcfzz3Jn5HQvnO+BgcXx6/AuieUB211sXluG2zGVcoqYa4VznGU8qj8MCmHLTTIYTyojOOhtU/vuH49+mr99vLc3OCcOOMM2Dux8/Agi9fgIdvmwH9+5Y52hg6qByeuvdqWDTzJZjz4dNw1QUngd+fvBvo/5gyypsIJeWHUyYwQ5jD01UoVR/K2nhbyUxHeiWTvY93JhhvT+gmtO32VQi3NJVhdDpOam4O/UQGmE+mxjbTAQ44pRukDWrnoBw1ef9lTwIMGZ1k3ygDhBSTN/pQJiGUqF7axFDejw6FMh2Td/u850amHwMNY6Y4E4ETVP9CPP/iOMPW86E+Y30GQtNQ+Sw31sRzO9KzFlEIpUq0VYIZCDpVSvHiF3PPQ2kTSlIo44Qyp3IVmBhwh0E/GBCEbXipqWSO72mE0m3gSjY207OVrg+l8ii2JrE5KZQq0lEooR18KNE7qz1Q5DPh2bEmvD6+fYnUhAKL+P3UCPB6lVQoAWBWvSFIO6qXiJBpQH3UIpR/HmTCl7UAK0PxtEFktsZzpRJKbG9vJ90Qv1PQDvpcUlBOriSUlRHrevULmLBDkQmH9lVPogn3bBKFUwaii0P3k38LMMhoWhT2LOk+fct45P5t4TKYNP14+9/vT/qLvezai0+BvXfdDk6/5BY47OQZMLC8Lzx6Rzw/nc/nE2QyJxiAg0+8BM676i444qDpcMmZx7bRh9IH0EQm75JEn61oNE5K0zF5IxnD38iMHomAmUyh1Ot/T90b4LBzoEOg9mPSrgDTjwEYv118/0I1IUKZzOTNjLLbQHFNcA2o8VIo41tlaPL2uU/ErlHekmg5FMok3uuh5njde5HAW1co8f7zdW6lHLd8jGqdazwPRH61yGyEjwg1jgfUFgXOoHqL65NFhNZVTeD+IMQotZB9XiLuCiWNIVElbRCarUMtEKxaAyaau8kkLkzeOqE0erbJ2zU4MVlZ3cxU73y3oJwMFEokOjqhzESh7A55KA+WpIqi1NsKNUgGSRym+cHUPagY4vHifpBAkh8jEsqGmCFM2mi+frvaMlOrUd5IKhFEKMkvUgf+3hg1bN9K24cSfVx9pvh7Y8QyeX8+MQYvjosf9IvDN9p/j+uG8W1D5TD1xwFZTCij0ShUVFbb/6qqLdJVXFQARx+6N1x7+yPwxbdz4KdfF8GF19wN207eAraZOE6ss9u0rWHspsPh7MvvgJ/nLYGPvvgObr3vX3DiEQdAMFlpw3RqeYfDFpGyfSiJUMbEwJzchzI3/kaPgxOpnA2qQhlIg/AqaVVoEm5nONIXkfpAn1TSTSWUK+YDfPpyfBtbRWFC2W3gmBDdgnI8CKXXJJlu2iB9Ik5HoUxp8m6OB4s5fCgjqX0o7cm/fT1xTDUJua5QomUDX9JEfW1ppqasDbQ9nS/0qcbt8DyQyZvOhW3al8RSMXmjqli58+HxBilYyS2xuUOhlGmDkGiHW8CPYxQ+60TqhUKpuUv0dJO3a/aBNNyR2hiUk25icxFx7EH40kGbgnLaiVegKtieGJkbj9pGQkmR1uRDif2ujwH0l+mVkDCSQokkEUkfkk5Sj4kUIlSFcqw0j6vA/RAxLnVRKLEtVCndgnIm58fHuQntaP5vL5D/aXtd9/ZAxq6om4wYAt+/9wS0hMLw3Zzf4KZ7noJVaytgq/GbQU4wCJ99Pdted+HSlbBy9XqYMmlz+P6neTB1q82Fwrmhqtpe5+Mvf4BbrjwLxo0eAXPnLXbdJ6k2hs8PQZe30bBICWRCrLkBjIISawBAEomfZgz8Zgxihs91W7F9MAeMcIsYCPz+IBjFfQBvpUBzPfj8fghHI+CTk4xbGyE5uBl+PwQKikBMI5Ew5Gjr0rZe/UgHvpwc0TfrfFhCvD8QBL/fD5FAEGKxKPgjIYjm5IGBA21THQS/ehNCux6uKETWCBloQ3oW2rYntaFeF3wBoVcC/Tq6oS3XNhrMifs/+YyENsJ+Wa3X8Dn6EvX5ZESpT1x/2r+bD6W6XdjApwXfP4KOyc/vD4h21GMJo/qGqqOYm3MgKtS4iKcBCJ8jQyp8+DxgTwLYTszaxkC7nN/9WYwEc6wULT5fuzwreG7E+SkoFs+xY1legXXOm+rAh/v1+cFvmhCNhMCXW+A4LzE0MeP5aqgVvweLSiHiD4ARCYFJ5yIWE+c4JE38YtyJRcWzGtnvZIiQ5UScl4BYjv+igaB1zcqHgYF+kcEccd8FcDwzY0LtNXLywUTTOpJVSX5xTDNxHc2n2p+TK44rGAlZ7eTm28feHue0q9uQrzYQzMm1n89gTo6411zXl4TS5/OL+zBVP4oDcU9EvK54TU0jBn7DkM+QtTwgxI3EpwDVNUPMV9Z6TTEkRrRtIvRzkOfHZzyzsaxAKIBRiIH3flJBPRdbFQDMbwLYJNfqD7abaRsq/jLMmnPWhzGhuCFIHQbHWH6Mphiv6qMmlAsHUlOcw0bTgBK/ldg8Aj4IiSfPtK9l2Mq9IMgUHnPYjMEQMew4rwm2FRL0PyYUSjyWqGGA34hCgc8Q/pUWWY1fT2wPjwGvHb1glAacYy/h8L5RuGpoFHb/JQjVUglNdT4yQbI28vx4TqyKgMmue1v7gduFtDSM7UIov/9pPpx/9V2waOkqGNC/j/CpfPWxm2GPP5wtviPJrK2TyX4lKqqqYUA/y7GhvH+ZUDVVELks798HYJ7HjuUEGQgEYGiZ5iQBAKsCAeG/2RyLgq+gCDAGFSVtfEfH4aQ4JwiVPj8MKHavgLEiNx8KDRNqzBiUFRVD/dZ7iIlgSNAAf1kZrMaEq9IPy62N5f6AGD5ygjlQXj4IVuLfEHPtq1cb6aK5uBRkhW7Iz8kF1FVLC4ugtKwMKvMLoMkwxc2/IRCEnIJCCDTWwICyMlgi/Uhz8IG1TiqU5rddx+9JbajXJZpXCMvl317XMVUb6aKuqAQ22N+MhDZWB3PFPY1EQu1LfUEhVMhjx+tPaHZR+NTtVgVzxD2Qn5cP6tPap7AQipX1sB9r8L6PRQDjmfsWl0C9PM9eiYMKzBhEpDkZCWp+MAD9yspgvc8Q+8rFCdofgCEu57SioBCw1C6+mNI5aMuzsjbgF2NASZ9+UKTtr7asL1SaMcgNt0AwvxDq/X4oy8uFWjMKecWloBYtNaUpvjTSBGgEKx80FKpyc8EfaYGwYZEcnBjxHC9HkojnFtsryIPVOG5Fw/ZLoDgvON4EAxDMzRHXvd/4KbD2oLOh/yf/hvyV8wBDg/rl50G93wfRnFzIKSqBpmhEvCT7cvNF+31zc6E5Jwj1fqSecZSV9oFKrMiYFxT3b5+yvgnH3pZz2tVtLPMZglr0Ly2zn88BZX3BouGJWC5f1grz8qB/GuPxkCK8Y6yr7/f5xTXNDVRDoc+AoWVo/VovluGcAtZT6YTPD6UFOFdY1q2amA/65AXltqkxqLgIhvpz4C/962G3whbYf1m/lNuUF2Cfw+ATfUx/rPI6Fzm+JlgZzYGxvhBM7l8C6yL+Nl3XvcusVFtNRgCKc3zg95kQNP1QGEDRJQYFufnQYrTAwFyLGKPaGPEFoX8wBrm+MOTlFYDhx3MdEsuGlvUBvx95Q0gIRXjMpq8K+klircIXyIHiQrweG0XuydycXCgw8drVQt8cPzSE0doQhT55SIWsrA2j+5RCs2nA7OaI8FPcIjcCAwvzYWhE98U24enNrGOb1K8YFoYCnfqsDM7Be34j5ObkwNCykla1kS6WVOKo0s6EEk3UhF8XLIUf5s6Hb95+FA7eZ2dobqF3xw6AVJBQnl5V7SSk4veYCZHmZjAxjYf0R2tutKbKcCQEdfi3PwBLTrsTAs/eCL6VCxzbR3wBqGuoEyrDRn8uxAZvKn5fs261UFTCLc0QkZLF+ro6CGtsPSrf4EKmCWtbrKkDt9H7ikwfL6pbG2mfij7xgbMpYrVR09IC9dXVEEFfz1AIqqurrP4EciHc1GT1A/eHb3YYlSrfxWqamiBCPm6tUPWQyPSUNvoWFjiui1kmHVQiYdd7Tkdbrm0Unx3Zd1Tj9TbCuAxNqoYPVlbXCDVebNdo0bqapkZx/akfxYMSFQX1GER7SAqjzvO1sbkZaqurHcci7hZ8NrAwS3OL1U0yp7qgCdctsCbPiGlCfXMTNFdXQ2zO5wBjpkKocq1IfeN2TiPSaQ3fhnHfbX1WUNlA1IAfqrEP2+0Hvl9mglFfDVGUSULNEGpuFOMHPhvVDfUQa2mBBtN5/kihrF2/Snyuj/kgGjPBaG4CUz5PkbB1n0Slmbu5pRkqNlo+WDGMIi+JE4NIMA/qmprAqLNIx/pNp1jnHwJQ02CNW5W1tRBragKzoExMonjOkVAKhRjXrauFWGmz7dvtm/MpxLbaFarD1jVdU7FOfFaFo1Cj3BttPaed0YYZzBVKtxvIr7GiMX4PrmtsBJ/HMxqV80FDKAQtaYzHLTnx/rREY+KaNg8ICxVLvWeb0cVK4pp1RXBUSQOMzzehPhyFCnkNEZUhE2KRkOcYQn0g4D24qsYHp4y15tN0xp6WPKncmVZ/WwPqR0VdrTAFr26OABQB1NbXwqpmo03XFZV/gVhEeL40GABVzREwckwRSbSxqRmqcmIwVJqVUVWsaonAsHzrXl7X0Ag1QcwbhGOXdU5q+lvnvyVmHXPD4CiUC0LqRHVLGJbV1Me/N7fA2gZrW7T11YRi0McwIRyOCbUThcrm+mpYHwuIgKFfGkwYHQRobMZ51MlxNpPnXbSL56nR16nPysBC6/zUNnvfX4iCgA8+GB+Bc5f6YVFTDKoimflVZKJstin7EqqRi5evhlHDB8OnX/0oVMKS4kKHSlnetwzWS1WyYkM1bD3BGf1MUeAVG+IOsMlKL7pLrwaYwmcpZPtQmnJAMqNRiCpRqZFJewAs+825eSAHYkhGo1GIKc76YdouEhYmMfFbNJrYB0l4sZ8R6bNkhkOeMrFrG2kioPgOmfJCRw2f8G0V/lPRCESarcHWzCsQJjmxL2mKM8m30zAEAYtopCJT9KQ2HNeFAjMi3tcxZRvpQl43cR8ZRmIbIjAmYplDcXCmyGnptxeNxazrb6+fOGCEcCa2CwBY943uVxxFk69KZDGYDU2q0r8YTUViW/KpdEEs1CxMuqJ9wyeeP3Es878HuOkEiKHrxYjN3c+Rsh0Nnm15VgwZQBPNKYAo+kXvfgREMSn4Gw/KQLxm8TwQKRPjBJqxye9wyVxRvpUUyihWucFbAut5+/zi2bL9JGOyn9KnMhaNiHMhlslPG3kFEMPtZDqmmLR+RItKISrJbASXiTyWqOgGwQi1gIHuKjLIxloeH9diGy0CiSZ0vC/CuBxdX/xB573RxnPa4W2M2QbgD+cD/PMCq0CDByKKGTYinh+Pvsh7Cp+UdMZj1QkEnwf8HV+MQN/eNGFuI8BjFX54o6UAWlqa4OYRUWiO4TZxolEVMYUPZdrnKhZzbJ/OdtKFUvhftvWa0NiyUUa9+E08N6kJyBVDYzCpKAx/2VAszmexYV2hDRGrbjalCcIRB/0fm6KWqh+QpLA2Ytqpe5BQ1kVMEXmNqI+YUCfPiUgZFMXzbK2LBBO/t8Qwz2W8P8tDPhiRE4OmqAk1UnhB4Hr1Uh3CoB8cF/E33HVdFMtkYpR7FFaFDRGygS+b6IcZALwuzmOeLAkvAt1XQh7OjB31rPjovpT3qRcmF8RgUn4EPhlvjRc5M9N3Y8gUbfJ+L8jPg5HDBsH6DRthzq8LIRQOw87bTbKXjx45FIYNGQDfzbYI3Kw5v8Hmm42Efn3i8v+u0yYLAjp/MRkwWlkpB08uDqLkbE9vuDIox4ZbOTL0jxRO7tF4FOcXr8eX47JkUd5q0ASlKEkWCdsaULuqEz+RXzvKXOahpJyaGIyQEDTAQTlpgUradVBwlQMUnY/3sGdgDL0IpFN2w2Wd4y6PJ4SmY0snyhvvezsDQsD6niwoJ4oEzSXKm0ABY24gEt9eeShlih/xWT7c+pFyamLUNT4nIghH9geTjSNZpojsWe+L54YUSjGmoNqIL612NRs5ttCA7hKUY0evq1DTDNH+ivsp5VNl2iDKQ4n7ppdGsRzvF+Xc2sclc2DSb+lGeSPRVlTULsOEnaxPt0AqFeo46FbAISFzQHsnNjdhVQjggXXW9cLE2naUt7JeVcQKLEEv6MNE9LTV6NH9YyLlC5Iqx2G14tanQB4qPdgWUBu10cwi1P86go7PwrptY7B2W8vvEdvEIBsRWS1ImmGn+YkH5cQ7LwhnDP0W499xe4RQ68E9KIcSn5fPCsLMJuu6IxnEtgiiqo78jgSUAnyQ7NI+KMk5OpNg30QidJfz0CfQusCr9kJumkE5kwvNNuc67RBCefUFf4IdpkwQJHHqpM3hsTsvh1g0Bq/+9xOoq2+E5159H6696GTYcepEmDh+NNx53Xkwa/avIiAH8cnMH2D+4hVw7w0XwhZjR4mo77+cdRw88cJbEApH0qiUkySqFQdXJHE0WdEAKxIEK4+4OplhTjcERa4KQikn25+/jK/nVuJMBUWI4uCfKwlpskk3U2y9B8AFD4i+RTffXh5X1IVQKmmDEDKAwlrfSSi7UWBY9wS9eHQKocQXAYtQuqcNwusq++EIPjLcE9C5ETI1LyodW0KUtxuhxAhjJcobJ3pM8O0FtX61kQahHD4OYNAm7Z/YHIkvZXxAQlY+zPmiiX3AvogxI9dJAnNl/0QaoQjEiJTgd4z0JkKpRnnTGENBb0raIFMeb+D5v8f7R4SR+oIo6euM8sZ/eG9IE7DIp0sQ45VybumZx77S70iO0y29eOpNAGfdCV0OJLbpRKer47HXy36qggEuyMsgsblamYaIDn6qE3x1xKrSctYgE14YF4MdJE8+WaZ6UQmsOJRW3PpEQtuDKKCfYWsIpb29YcJepfH70i+n7RqcWpXIarVaDZI8VAcdgTSmUjnHBGigdyTlPCNoliWSiED1EoN+6Hc1/ZFIbE6VeGQpRkqKTn0YhqZ42W/8ifqqo8yfeN46E7lp5h+doEW/d2RfMzJ5Dx7YD+676WLoU1YClRtr4NsffoEDT7gYqjZavkDX3vYImKYJD98+Q5i/P/7ye5hxYzzxeSwWgxPOvQ5uvuJMeOPJ26CxqRlefOND+Pt9zyTfcapqB4LQSYWSBhFFoTRUOZgmU6zNe+QlAP++VZoc5QBO6o3qw6MnO3bbP5rLcDJwUxLbihHjrc9Bm4C5+bbKxCyPpajMqZqoJjY6dl2h5Fre3sBJeehmnUcoiZxghKlrtRppEqe/UyBppRy8121C6VG2T4VIZC7Nq7gcS5JSwn83qLkV6UVLBd6buJzu1eOusH6/6YT2TWzeZ1DclQBJFdXtpucTzwG6uQiFkgilzCtZqhBKVFxpOT5LqFAiqaY8lLYimUShzMmHYPV6gDrLt9leTteUrkdxX2ceSkobhIS3rlIjlDIPJYHGK+yrmsIIzzMee0087Ktbo0i+BBCp9wC5+wh4jc3q72mOd+pkS9OwyIjg+MUiG+qdjaQHIeJulfm7UZKRAbIrRCCJqFkENr5BQCiWmY3NdCbahVAa8Qoz8f6lQrz/+xS1wJ2DI4kENWKZk4lQChJHCiWatZVbOyxJJYHyVIplMY1Q6gRT1FI3bFKPJJGW0XK6VljbG63foZgBZQHTJq0XDTXhhY2WeV6vE64Cjwcr+OBne6jDAKa4TzAaPh3QPlMZ00m51bfrCGTEev58mfKG7QKM8r78pgfEPy+sWlMBx5/910x2G1cmk5VeFDnkFN8uW6FEohhx1j/GQbbfkDgZs9dTTN4qodywGszNt4NwSX8AN+dXbA+d86mSSHsSyrFTALbYIX6cBGGay4srmKO2ANiwKl4OjmCbvOmJa0fltKfidycCTNy58/ZHiarJzzFhuSR1CCRJeN3xBcJrYEhGyBwVYvR71HBXKJEY4bOBRBufDySU+Hy5mXLVMqWuhLIl3g8kZ459taNC2W+Q+MipXA1hPE5qm0ypdE4dhFKzctgKpUI48fkRlXXwJUAxW5MqaPu3ynVtNbQxsZKObfKW+8PUQvSSSOORMHlbKrGhbi9cJFSFUiGUtloaBRg0EmDH2wAeuFSQ0i4BElo0ZX/xWup1SaFVE8G7rpepQpneS4qqENqJzeXv/iQKpaqQOYimTD1DtzQtI6KGZNNoo0JJ27SFUBb6TLi8vA7+KdkWKZTpEMpBQWc7buQFid3AHKuvDoVSkjZSBy310KrN7UYoiQzS8jihtNL+NGlKJh5HyEOhpO+kUOK/35oAJhaAKDuJbg1k8nYjYWiSXx+WhLId3oFPGWDCA6NNGPStT/ietlf+Ud2w221M3l0FNSjHFSKBsulUkzBvm9hYCWJA4OA8aJRzEkEI85Vi8lZVvm/fFQNd8+DR3vsXDvS++ICoVdtoNQ4/T+m78taOfVXJQZ+B8UlOJdZ23knF9yqdes+9GUrOwKRVONoL5HKBuQVT+jH6LPeHM/DlrhWJzZMRSk+FUibRLiyLJwN/+DKAp/6WuL5aBECYvLX353Czt0mzNYQSleRxUxN/Ly3HVA8ibZZol/pEhFL4d0pSZxPImPQ7VL5Hw05CKZKRYy5I6a+smrjF8asE07TbN1RFUm2LrokMqrGVVLWSjiD1mAkgicmbziuqmXZUrbxmeB3Kyr3PoXofYI3zTSYAbDKx/XwqDz0HAIOxkhWXSCCUyRVKR4J9T4VSGYPTvKfUydZObI7veVLR8lIoSVHDddUJHskLkjLalBaRQomfqt+kTigpo0My+KUfJvaptSUCj+oXg5P6NME0Wf6wTgbi5PtM2KkYa257t7tpntPk7UUo0YfSQSjRBI5Tp0IoiZgTcaS/MfG5SnRJdaRzTdsRWaRKcLg+BqAQ+UdyqbatqqX4791qq+zjHiVWoI4weSsKZZ7PhGfGxKA8YEKZ34QKMkIkOT/pYqeS5HXFW+tDqT91OjneutAq4ThUmvrRF9bNv7fHEEq7/JvXgERBOW4KpWqGQkUEByGchGhitf2npAkJFRi9Li+2W18NYTRJJe48HjQhKmh4lLVLVrmjr6WmpIRKBtyq91DfVWKt1+62lzGh9EQFZhKF9JXm0v4QOutuqB2/Y+v2R8FUSADcCCUSGlKgcLl9j7n3zZWUEmyXjlDi86RNuia9gBGZKVYIJZpQV8n0W6sXxTcSCl7QTsTukHHUFzU3wtAak/cJVwMcdm7i77K6jFD1BKHUFEqqViOU/ty4qigUynyF1Kkmb4Xk2SZvnVBqJnD5vIl+OBRGZVtsr2pt/MWQlpNCKdTUcKIPpatCmef056RjI0uMG9Tx6E9/AzjqUoCjLgHY4whoFxAxTfUs4XHSPZAGocTI2qQv79QWno8076mgh0JpaBNxMoWSVDP8pOTYpBLRE5enEBQ1k6hOKN1MrTrUbVqrPh3b3zoAIhXo84goDwB8MiEGd49KQiiVdD06WVF9MoUPJU6VksQRkabzhCCyRwojkUQinPZ6LkE5tK7VD6m0SqVP9b3UFUpsC88b9r0xalXOwaTqeM1EXxUfyl2LAY7sb8JZg02hTKJC6XbcrQE1ofvVeoHujVS5TfRAL/XFCIHkGUH+vacOjGXUj6wjlEJNw8HRc1AwnD5LKqGkVCn4J6oAOPDudSzADgdYy8nETQM8Oevre6jZABE3QkmTe4JC6T54RgpKIXzOvVYNbsSmWwGcfqszaAIjUk+6Lq6WEpTvhpvpurhPfKLRFRNboWxjWoneADxXWHbzs1fSC2pAElBYAjWTp7eDQulmdg4qQReKsuelzKSjUDZbuVmd22nPl1pGFJ8vIiWqD+V9FwI8e3P8Oz0HRHzdfCjbi1Cqx4l/U8lUhPTRFEROEBV5LLSO6JtWu1uMIdJXVH43IppCSX6N5AOqE0hbsaQZj2qYuyiUqm83+lgiBo60Ppvq4uQ1GBT9cBDKWBpBOfhJbglJCWWx+0trs1f6+lYq/sn80BHqeJeSUGIFG19yQmn704fS96F0Uyil+qeStUSFMv73WnnJSY3D7XwaCVB9KHWFUlUl1WAQJG67y8lfhfq0tMb0ivkUdyi22h0sTyWSLiRaSJoQ+/fxJpSjlUuVb5iwLgxw0VJD+E3Go8atNDyYqkf1Y0REFaJIJF0PsmmQiimtR+fbJoryd1qOyipCDfahdnXyr5q8qexjIb7HSfUP+0rn1XZdMK1SjhWSsKZD/FUg4T1/MAZpJZ7XknQVStIVUtzaeBw1SuonnfwigUb0lWmafG14OckKQmkHzXhFeYsJQFEoVXJJufPwz7VL46ZwAhFKUogQqg8idaF2A0SK+jrf6tE8RYMa7g9redsR1+6DZ5hMWlP3dg6cKqE8+AzLLE9+nm6DrFsUOSoBmjJif6fB1SbLrFB6As9V3UbrPkjH5C2vS9J68ekE5YhMAdojSfWzKRWUw2Qd9IjyTvJY0/0uCKW7Qhk+9BxoHjDSkYtTEBgiY6rvIyqVqr8x5WUUgTceUd4IqjXflrRBFBGM2GYvgPP+ET8+m1CGExVKVGlthVJ5CVXTACkvmaZNOCWhRHM3uZfoBJJIIp0TUijJhK3uS00thpHzqPyizyNuiyRIVSijYWdwodh3iqAc4feahkJZoCiUah9TEcB0QONdOu3RtUvHhxLvHbpPUgXl4Llpjcmb0gaZBuxTZqXCcSqUzlQ3hGXK4+BFKG2FUpqB7S7je5Hy+KpE5betY/C/LRP1KHV7bC9TYKlFREPMgCGYQFxR8rBcIWJ4kqB71eRd7I8JctcoSRn1n0zV8VQ9Sh5RRaGkyxTSTd6aSZwIJBFGIpakPuaRQqkRSjeFEv9hP5E0YrsNWEdcEH3Tyl8qFEqrPRqxTCUox8vHMhl+VwZw2ygTrhyWeD3pnKcCvWykIn54HBWR+I2k9xXJPoLqmRNBbc3LSXYQSopyTZqHEv2fwi6BOAYYmOoDm8FUQKopPIFQapOBitpKiNCgjNucfx/AH6+NEwBh8lbMkbpCWVQmJtmorCJi+8TRBNtnQGI6I/3NW5or+3/0bHwyQlPZvecmTgj0qaZ8UY5NKwbCSFAMUZVTIpaTgZLZt5ZQ2mmrFJM3ToboJ0nR5m7KnsdEmtQ/lqJnMVk5HRvmW0TgvZuTB+aYbaBiuhJ1TQol3Y/JkvRSWiox4UsVUIV6HCppwHNIgTKZEkp89ik6mF7MiFCi4kg+lOTKgAE7qg8lQc9ZK91H7GIHgmDKVD6eUd7acyefU8NtXw4TeNiKAkfSjuo4tYX7sd0OVDecsHuUt5qHMl1CiZYNalO1zqRK3eMG9MFUX6a33z/+d7oKperHmgAK0JSkPqlCSYQy1CYfSjeTolUdOg6VACExcxBKXFn+RMTE4UOpmry1qFxVofTSU1SFivzv0HSttpsMqEwheV4e9st62BaJQpKnJgv3wqRCE9bJ273YZ0KzaUW3Y7+QmKnEjwilatK2CKV1ED6X8ymCcmwfSZkOSC6vl2RI971EVwKVUBqKryv2z+FDGdMUylhcodSjvItEeUeLUOKxUBR5poQyX/aPFGAVaG5vT4USXzjWR+PcSSeg5INL+TfpPmtNbs2sIJRigqS0Jen4UKoDvWGAUbkaRj18IfjWLI4P9B+/aCkC5FNGeSgRbiZvrKpBA+y+J1mfOOjZJm+ZNshtkMOJ9Zx7IDr9GIhQbjxSlWh98qOk5W5J2OX3/NULnBNXfU1ilCk9QjTR2G/rRKiZUaYkeGoKnGSQfmpUcSUl8JqrEya6UuC9GFOCctCMjv+238+bUNpR1mnkobS3kQqW8KGUx/bVm1ZVEtxO3uPCvcMmlFIts33Skic2Fz3CydwtDyXdf/h8qPc3kgkkT/hSmI7JG8/DAafK/iEZk5W2hktC6fcLRQ8VSkFuse9EKCnTg5tC6RaJreaGpHvCNnlHnNdHfymVYxISSsdV0RVL7EdtVdzcLc6lVChFdSJNodQTm9P9qqcNovu3SJJGN6iWEPVl2oPU1Y2ZCtFpB7m39efbLAsLpTdTiSz6d+78e4j1lzlBBQyAbX9n3Q/0co/3Ir34zHhKbKPD8aylUijFS0qaPpRKlLKa2FxHQtogD0c2L4VS/e5PU6H0gqiQIzuJKhMG5iybEhMKWDpAEroxilVtfDBE+lBiv0VycQehTGwPA1MmFAB8WGsdRIkPK88YNqmm5N/kk4nKLPktErA6FKmGRGYwlQ+BzO8Ok7emUNLx2yZvD4US0w4hSaRr6wjKUUzeRT7LhxL7hsdD5IqSreNpCcr1hYKZIZMKUHtqLkuX35KB+kRt9QmY8OGWUegvTdcEvL8alfOpK4+0X7pW+r3a4wilnU8uZZS3SiidFWGwJrcAfaKprr7aXaF0Ky0XaRGDmIl5+MZNsRRG3J4mG5HQ2R/vo0pEhli1wc3+wyCqJltW1yPfqT9ek4RQFjjTl4i/8dOMTwR6vkLdfE/rcZS3jXBeMawcKSdANY0P5RbFf6fcCDBS5gPVIaPv8YUjLZUSS8td9FD8O177dUudJm/b/OtzEhb1nvBSkJJdW5GoXKpbdO+JWuFmPCWRuq6bQpksk668Ly2Ttz/Rh1KtHqPuC59DUoaT9R+JJ56vYWPihFqom+QjWZzoQ0kmbzTz4zNLriq62dlDoXR8p2A4ukd0QkmTLo0hetCOeh4cJuxIPE8lvlzo27gF5ahkncixI22QspwU3GRKL0X0u91fGPUtx8oNexwL0V0O824PySRGdmO7GF2+UgZvDRwBsMthEMHAHwL+hj7t2B4plHge8N6g67u99HdXoaasSotQtkGhdLndExObO9u/a7UB160wBGHBCV83dZNCh0qV+sqqrotIR/nCEadSmjRRZSKV8fdK5ZpkQBK6MQJQFTVsUmGbvBVyQqrqjSNi8M546x7bSk6fn0tRvcgXE9sSsSsNJPoyinKJCQqlriTGl+PfREi/rncqkbpPpW3y1kztalu4F7t0o5IWiEzeGOGOCqVdKUdRKInsoYqM9wopmG7XKWCYsGDsejikj7ebAhFUVZlM2+RNU4X8jtHZu5YAHKxdd8sX1IADfwu4KpTUd/KhtE3ePVWhxMHfzsHmRipJCVH9BvXoZntdiE8ASK5oEFNVTTdCGQ4JXyoTq3rgZPXbN9agRgOVrLtr+6WpgxzWp5V+mLbJm7aliRCJAqpCaH7Cic/Nj0iSCct8Jo/VrjdOExgpszRyuRPKtic56DlYu80hsHDLfcGk862avBH4EoCVVsYppFOFWt5O9QPzwuh4eVJBbrA04LplzqAcnSy6KpS5rs9E0ihvSkGDpNAmlBRhbjjat1UgOw9lirKLtC4lnhZmZf1Ow1f6FqvvKjmmSGPhi+zRf1wHUyYhISHi/stX1if1W60epQflkEkXr7ObQimqbamEUualdLiSyHycYrli1bDTOjldS+JR3rpU0uKiUFY6CaWyPCEoR09sTmOC6reqKsnocqPuH4s60MsrKpREZtWXBfUexKjvg05PkZ1CG2yxL2gCx/y4COV6i3ro1G9SlslEjcFAeO/htqJPynHS86Ga1bfcMTGAUe0/3m9tSRvksp5XYnNa9+JlPrhupc8mjmQ61lO9WEE58T3gd3UiT0clQgJQJU2aWP96FHk5pElMkERWRQzb7KyavFVyQ5VhLh1qwt5lllmd1FRKxl3sR4XS8kMUbfsTiZ2uUMYUYuhzVXwNWBUyYLPvffDQOiOhMpG6PhFF8gskIqsTVTWoB/9GshxwKJTWNcYniFIcYbDUfjI4Ca8nVfnxUignyAo1fyqPehJKJP9HyQh7IpcqycxEoSST9QYtMTpV/JnXbCSNxKd71N/TFUorylteFDcFKMHkrSgNCQOJYgrGycUR5R32ro4i2zZJJUQ/JxywVIVSHejwd0zmiyRk2oH2tjGVaAplRTkefKPH6h1fve1eLYIIZTQSJ9i6z5adAFszeRNsxZIVyjhMZzSqavJWVS8sE+gGNT+o28TmBbxHaJ+1G61chUSmqB3bSz0ZoTQyUCilnyI+L0o0szgHCQqlRiiRjHplCahcbZEq8qFUA1l0YGAckjI0PRNs1xMkRS79x3sfVWICPXdLf7E+6WXA8VKgBuXIa4p9xBcA8qFMFpRDPpjqcZBZmX7TFUqbUNLzqPhQqsDlug/lqoVW/0jR0xRKB0FUgwjFd/WFWnd/se6V2Fa7xr9jpbAhMq8u+m1WyTyYKug4iUBL64pBx6oGRbn5jeN5V3NsKi/ILQNHOc/XgBHSLxXdMTAYTiGU6nHSS5DqUoTP5z4nJPYfze3YFvoLtzFtUEqFUlPYCEQoSX0i5YxUICpHSMBJXZ3I0/FjQ0KBhBYDRFBtHCHT+CBRpDKCzmM04drhMdvPEJUpVCjDSu9JoVR9KHV/PzSrU99tH0k0eUsfSuqDWK4k6tajvFWF0jZ5u7D4pS24UBJKSX51gkg+ln9ZWwJHLUCN0XkC6ToRoSe1lMg3/o0Vcwr9pjPK2wA4vJ+lACKQaDuq/rhcp+1kBPdGJcLaLZDqX2OcymQ6fqsqEaS2ysmrTTt3fnmvUoolva90DWm/Ro9XKB2l54wklXJcFEr9ETeURMCCUKpmZG9CadAEQevjIIUDLQ2IapJdzMuHb9lYMhEHbsS8WZbCguurEZlqxQec6HBQpVJ3CQplQaKDP00yRCSpbV9yhZL5ZBx+OUGaFMVsmzPlKEm/Y7CUnkOUrhsRqXQUSnUipOuPhALvYZr4cr0IpYvJW58sU5m8yYStp6ARhFJNS0RBOMr6XgE5D88AuPPP9ktZzDaPu0zHospOLsDWu8dzWKq1090mf6xShQRh/vfOY8fnUN1eVShNzeSNfcP7X/g+S/Kim7y9IrHVtEBqKUZS9BIUSiehTEzw3uI8N7je8t8A7jgd4MePZPvOXLgJKqfDP1Up7GBHeTvPfZR8v/V7BRVyuyykMhvRvUD3HN3jRDBV6wrmAlXTNiHoPFH6IUWhDJcOcJ4vMZbKmvbCdJ8TT8bu8Je09mmiWq7CLTAHrT3oW0vqexsSm6dSKL0sPmFJcMhUapspiVBqFXiQ2KRSKPVk5+Trh+lf+gfAViirIgCnDUzs2X5lAFcOM+E0WU+8n1QoVSIiCKVMjUMgcqginhbI+izxxZwKZcBdoVSr1yBp0xVKN0KpgvqqR31vkI9MdcwHr2+Mnzy6/ERkqTu4utoXJKqkUIqykIoCqZ4LNOXjciLHem5HxDipUA6QkfNq0nm3ikhE2ElpTAX9XqLthCl+WlSkJUJQeUs6zoCHD2WCQtlTCaUw4SU1eUuF0o6sVE3eHgolKnU4qBNBEIRSmwTciBhN9DhIqqUWaRtR1aQRYPVCawDF7zhRVK0VCc2Fjx1NgkQgCZRKBfuOx5LgQ6nWGPZQKG3CmMrkzYyS4KMqI+TfSiZvXaHU0zupEycFhdD9kQ6wXZqURdogM27yJmJKkzkRFjcfSj0heTI1BidiSklDIB9KEeWttG9HNyumXTeCKH43HS91ZipCicvR7ImqnDjeAoVQutyb9JysX2Z90nNrnxelRrf9EioVSpHLEYl0RJq889JWKO3lUQ+FkvpFhN/vZfLWXAX0bBNueWWT+VAivPxT1aAcvR2d/NiBMJJQ0r2DbdBx0jnFACccz9RMBIjNt7eqFW0xzcPkrN27jXUQoWTnaqClXc4Sr1kwfv/htaOXca/ck3oZT5tQVkn/4FYQymRBOVqFElLk5jQ696ObvJFAIiEkhdKqlGPaBBBVKnUid5vUqY/Hl8fglAExu6ILkkIMsEGT6bwmgOUt7uZTUhMH5cRJXzXe6oofKJIPVCiLNJM3qZp6tLKdFkgE5VhkVD3uBJO3l0Kp7D8Z6PzpCuUqlwQtbiZv2g+a+XV/TUEoRZS3GTd5GxZZJ5Apn8ix23UqkjsZmWOKUo6haTHYuxR3ZjruM6s+uWm3T8nlty0yE0pZ6gFRCGqrnySuVJLxsqFxn0h84aB70auaEV0rO8q7p5q8xWCgB5s4lssEykQI1cTeXuZA4cOkOblH0jB5qwqlrqwgcCDECbq5yZrkiCDigJdfDCb2n97Y0VQqcgw2W9sToSRyq0dZYns4sVB/1U8a9nSFUg/KsV+3mVASfKSqDd7EyuWZYPKWygt+R19KJJ6olmGwFU6qwVwwKDLXK4UJpv8566749aV2bUIpTZik2NB9huqRF6HMaa1CGUr0vxPqaDzKG2E6CKWLGdUNuoqlR3nTPYrL6eVLHJc7oTRFGhoZBKMSByKURFbyXBRK1WSNv+N1xmcNnzsKGIqkCMpJqISjZJsQ6meOh8mbguTI5K1Hu2vPpaqU2r+p45N0O0hGKPW64pSyCQMQF3wfP3fqSw/dZ5SsHscvJPn/eyZ+L6gKpZoEndR1akM/BptQOgPKjMo1ELYJpcJYKBWTeOEIOpfh8+YWMEYgv3MV6JOOL3oUcJZpLW/tUwVO0urvmDh6yx98cMNK57NHZkYyZ+pR3aJSjvxuEUrTEYXrlguQJvrHN7NqP5OShkSRfPuQPKBKWOyyPZE5MpEiqUUSRYQDibQoOaiZvFGVGxJ0V9WIMGJ/WxTygsEtCUE5ukKp+lDaRNHwDIhSSRG1Q76ca1weIwehtBOfW5+UR1LtG6YNEoQSr7ESlINJ35c0Azyx3rCJOl5f3MbtOhX44ud5qLxd39kiBgeUWdcI3QzuWWPAb81xV4fFzQDDcq2AnpkTY3D/Js5nflSuCRcNiTlqqFNZTPJxJXJL+8d9iXyamsl7dJ4pVFPqO92jdH/23MTmlPg5WVCOWstbJQNekysSLd28ZQe2pFAoccCmicyedBWFEtvCiRInOWFqk4Qyr0CkUzFsQil9MIUi2aIoAVF3hVLkmCMiqSknqvLq1m+dUDKftEGR2THMmXfWnUopRCJ+krxghDBeg7PvEmmgRB5STJ+CvzXWu5viCDsdAlDS1yJCdM2O/otCKC2Tt61QInFF5GnEyWHy9kgEniooRyiUsUR1UfehVPMv6qUFvRDRTN5uhBKfM4rMxr7gNqoPpew/thE+7Rarnj2RC3mehbqLfdYVSuqzvIZCoaTvUVIoFR/KZNVrRKS/ZrJWl+O+yWeaxg7bp1r3oYwkfy7dXmL1oJykJm+tKo/aV2xn2a/2vWaqqXyIIBKhxPEL/cPx2IjUkWUkEgFTTWtGPpNq6jUVtluC8941qtZApNiFUNJYKPxeFXciN0LpFbSmArcRhBLTL7Xeh9L0WE8nOxj0gHWjVSQE5cjgD4IIypF/I8Eo0UzeB7lUqEHCQCoWEQrcL6qkBT5L/cL9IomjvIkYLEMlEmn/lF4G27NyQxpKnw1BDNW+opJJRIyAZlYks2TiRiABI+KG6Xdao1DScnU9xzkgvUQupwo/a0PJJ7aQRnSRxKsR+hSMhMcdVEzeeE0wpdKCZivinM6DGiWuk10693h+6fgQo/KsyH47qbqifv7QAIK0byJv722LnM/4S+NicMtIS+UcKI+ZrhERQzq2AsWEHVXuRTwu9Judt3UMLhoSV0uRRCPBjAflmD2UUCLSMXm7ljlLolDqUZNp+FCKoBwySasTvGryxv3jIIrriuhSnDTl9jgQ2gOsokiqAUK2QulSLcKORCffyXDicSUzrdnDIzNKgkhxowK/UyAKAkkgnlesZiLIiDYJ5rgolKisqT5lpKiJSdqXSArJrGz4wMToWTQhquqPqvKQGkOTqj5ZphOUoyfixtlRi/KGVimUaZq8yf+YniUXk3fT8PHxqHgyr9J5JmJOxM3Nh1KYvFWzsWrylmpYgkLpTD4eD37TzheCSBf1m/ZLx6icj0QfSt3kHUrD5B1xnlMvk7ft76mMFfKci6mIXlYQpBRSZDm9EKt+3rZCGXbmlaTnhtRhneSRgk7nWQlojNEy9VmioC9Ma0VkFtVVV0KpKZS47uitANDKYK+TG7dEqb7qrUwb9G09wIxl8UjZFFZZAZrESS1C8qD2BFUlUpiQUAofSmUiP1n4QNK/OHEYlxdX2Ch4BHM/FirpbEhpQ3wzMQbzt4k5jpEUSitdTlxV1COnEUgYUREj0lIZjpNMvfoMEjCduFFicjonzjyU8fNECqVlBna2q4KI4xIZuTxXajS/yKlVh1ewjwhG0kzeetJ1yiWKpHVNyBC/EaFENwHchlTBMwbGoHGHmEhgj2UmEehfqZqPS5UIcSKjdC1+bDDE+lQKc2QuwKBAfBwgP07cPq5QOk3sqqqMUf+ktKKbG+4Tr+Fk+SiOyXeSYUEqe3xQjholSZMnBkjsc7wVeWsH5Sh5KD2jvCXUSZW2SWbyVoNyVEJpv72HnYMiKpS5ikIpJyT0QTLIzEdR3qSc6IRSVyiVCc2e6JrrteAN3YnEdFUoOW1QHDG9TKZt8lZM00gehKlWT/aM6XfQL7FFqEg2wcAEz1gKkEDXFhUhbB+DtOi7kgYGXSJMin5GAkvklvqC9wTeexTY4uVD6aYMIuyqK1rgBuXAVNMGBVVC6ZFP0SsPpZ0E3cvkjXYd+Wxg1LdLUE6LmnCbyEijQijJPKpHd+P18PmtZOKqtcEtKEclcnraIDXQRSfgooMyvQ312y0YzivKWyeDdFwqtLRCdhsUka1eOzo+9bsaSETJvX1+MCm6Wy2NSNV58HjEWBqJn08a47AMJfolYr+wv3ZQDqnDGqEM5DrdiWQ7RqjJSnwv2ldmPzG2Sh9KEUjlt8ZFtO4goaR7BFO4yXvfWPxTvJ9HXAxw4l9dfDJlxaE0oAZXUGlFUyFKVFYR1/Myx7oSSvJkURRKVBAxcIN6hj6Qug8lAv0idb/K/tJfDtUyCrpownKHsn0kDphPkcgFEgf7GEmhJEIpo8RJqSN1UVUHUZlDckPbXiKJNfYN11dJWLPyHUkOfneWO3T6LVpuAYa7QukxjL1fY8DU2T54r8ba7oVKA/p/44OVqRRKrT2hUKpkGAmkkj6JlD08biRbeL6dhJISo1sdvnhIPGIbyTReA/WFoiJs+a7aKYekOZ0UyrnSB3cHJfbz8vK4fzC1g+edyLpNKF2ixL+YGLMq/tjR8db1PqbctO9B9Z4nl4me7UOJsH0o/dZkcuzlAFP2Bpi8e2JQjiMPpXaDvXIvwOf/cbZJ2+iqggqaeHDQwwHaLnXmpVBKQikUoXhQgyAvdlCOjGwkk7eawsjN5K32mfpIflFeCmUCyOTNCiUhIRm5bfKW5xrvN7xmGLyDk2Z1hUtCbkpR4+JDufl2iZWQKOcgBfyISGtLJTTR9wvvJ0x2rhM6JENC8ZZJrL18KL2Inx3lralYVDdaJQW4LyQXwifZPXLY6/6MR3lHvQmlIwBNMZu6FQcgX1Lbh7LYXaEUf6Pyr+ShVPtGCqWd2FxPxaP1l3wgKXBLJ5QYkY0uLNWS5JESRmOJtEYkEEodbkElDoUyZL2wIGa+oRFKWkdPGxSL/y7PE6YtM0dsHk/lg4RSpFNqVO59vOZKmjbFUoL3ZgDN4xQ44xZARqB7iUgiLQ81x60C6r2L7dDLNCmU+B1dTYRCSUE9MmUbdnfWu1YFJLeKVmJ7Ofa2g0KJxIICV9JVKMmHEhQzIk3YPzUAbJ6P351BOaQC7j7X+mNEDsAb4+N7w4meFC0kCAEZdIHpbvKVdDb1kmAOkuSTQPu3fe58TmXOTaFcKAhl3DyK5Jeqs+D6aHKnY1VN3kikrb/jJ5aUObdzpCuJXgol4kdHAJQB1S7peXToCiW6CajEGfuqOm6oCiUpv2GNUKom71Hy3QvJHgbUUJ/I/I2BUoOD1nlUt6UXhDWhuH8jqqdI+FSFkvaL5J7WT0YoN8N3Z8U9A/uOLxcnygj/ARgCoJw2vP+oHnyPjfIWUAniltOsiRGdx0WSYi0oRyu9mJAv77NX4uvZ7adSKFucJm99IlPTBpFCiX2kYAC5L6Hc2IEzAc3kTSmMJMEktejBvwAsmu3sM32iimUdqKOfdtSmDvvhYUJJQLWktHIZwMb1FtHTVUG8Lqj8EhlBAvH9B1YOREEorYnLUig1QomT7qFnJxIjWV9eqJ8iKCbux2iiryVGp6ovSEQOcCKlCdqLUOK1TaZQYrt6ahkilEQ4EeLe1ZTJZGUXrbMptrfLlLrJOA4CGXa+PClVTRxEn3xJKdcl+rVSipmEYKW4SduhUNqJzVWFMklQDvVP9FmrRCX60gywZgnAnWfErxUWPBCdl+cVl+Ouk5U+9PIBdJjrw2CYMci59SSAnz537oMeai+FUhnbWspHgok5H2d/ai1Doob3dkIwkmIRonOLz0VRGfgbquOq3xY7WOnREHoQYVBXKPPjf6NSKgo7aAolWYroXhRjaZNlGSClFNVRNehLlJjU3FCov7HMFMqcJInNkYzQWcJJOFnBKIKeExCVKJtQNlqK5NBgzDZfi+AMJIQxzLtorXdgXxP2VFxXkSTuKaKFLTJIiauRHOEyQShl6h4kGYdqlVNo/xSEkSPXpzyUeuQ0YlGzASMUhRLJjq1QKmRFbIeXRG6Hx6OTOCRSaiFSWvfHBoDzl/qdicrb2ZSWqHgaCQplxMUcL8zWmPhclm6kwBUrD6UhiF5kWvwZwuuA535jzOcgeytClulcVyiR3OP1wpcCujZIFm9a5YcxuXi2TIfSvbM0if+ENEP0xbSJpJ7HErMIUM9wf5ReCF8SkNzi9W9U0jxRrlS3QKOeRyjFAFdg+ZFVr7cGKT0oR1WXkhEnhzqhkEQvB3kcqAWhVE1ted5R3qRIRTRCSUEOVFlHKCeaQimivuVAjmqB3N5WXEgd8FIon7wW4Knr4v1//2mAr99hk7cLTF8A/NEW8M/+KB55r6bKoXJ2VOGFStThPYjXTKjMsm60XgaunzRfU3ocJXWKrVAq0blorjb7D7GIrRpkpvbFnpR9rj6UIpOAmzJI26vuHrSeuB9xNsqxsxCIKG879UyaCqXsr30e3Hwocf92ZLBUpOjeV3wonYSSno1w/FlRc4Ui6JmUJm9PhRKvL6pnug+lXg6RfhOfelYF0cPEY0P18OYT498xfRhulkl+UoJC3pFMJsD2pZT90F+IVWuGHBdC5cOt3zDq23Yd0Mo4qoo0vvDQNv6gCOjxC4VSViA65EwlX6Vm8lYrChGhFOdYGcPUa0xjq/2SIO8/8rl1USitvkacCuRfHrfKc9LYKtI7tUKhpKhniJMHShWUqQ+l6HYUYEpR3JS4St6u5f6YrVDiJI5kAlWztThtmABj5RRz8kKrc+cMNuGQvvF+iLRBIpm4IQmlaQflILnYodjpl0iKKO4LU+MgOcL9kVJom7xJ4DYBljZbkcpENhyEUssFicE8IqgnZhElSqnkRepou6lz/PDQer9rnsn2gk7wxf6V34QKrSxTg1nQ3CwIp2au16Phifjh+tWyghH5N6IPJhI63YcSz6vqKoDb4zVZ2GyIwCYyidPLAFbsQQKOFYQC5Jtrp/9xHiReA3LfwP7T8mXNAAPRL9bAgDL0SwW4ZEgsbvLuHQqlzP2Igw6+udJAjYMqKTmk+CDmz0rSppJbD9fX024oEI8I7lNMZIrJW8nR5lAoSXEgwmC/8UszDuWwk2REmFNJhcEBUuS7o4CNxLyTdkoXCtDQCSWaiYjEIGa9D/Dhc2zydkHMHwAfnmMkKiI3qLyGRLpQKaFrToQTSZAglDI1lJdCSSZtUpV0X0CVUJoxaB60KZijJwOsX+GM5I+q5FZGwtowMlAo0WSuJCpXP0kVUvOk2n1zz2noimgkeZS3buJWMxzohJLub1J2VXVW9EV5bsksTeZSJPkqYcTtdEVS97FMUCi1AgL2Z5KZTiV/zY3gf/NB6PfFq5AxUkXUe0V50xhgR3vHldwYjRtqonzFJcfejr5j3Xm0CCFwvAoEwScizjFlkkbSiPCtX259qgngqTStqhrrqYGEyVtRnbE9Qfplminsu8wfbKelonFbJ4zoYqL6ULpVWMuw9KJKKEWUd4YE5os6i3hMlLc+EkhEmUIoybfRIi6G8LkbLqOzV0v/QJUwUBoivFqocBWoJm8ZlEPRuqiyodKlHiP5UVomb2uBbbqWB4htbZS+mmUyMhzzVuoKZchlO0yvoxNKOk4CJmTXgSb0T2sBLlzavhSFovDf2Wi5BKj9pr+JeCPU/I3CfK8F7VClHD3fZyEplLbJ2/q9JmKZw/1qlR2fJJRK27h9WDHH6wEyY/IAfmm03Azwuqr5QvVa4Ega6ekOK+R3QbMhTPSorqI6/vwGAzbNiz8DPVqhNCjar+/AeC49QSgLnIO4GnBw658AvpT+Rm6wU/AQsUyu24nJiar20DY0cdIgiAOdcO7XlA9lwLYq3ZBC6WLyVgmkPsDT7zRY0yTqGZSjIR07TS9UKH0xTb1SrxleU0E4pQ8lBZOgkid9KEU5TJEOR1Mo6YWHSBp9pzQtqAApLzYxIqBfvKYo7sqETyRPJUZ6lLdwmvEgI+LY1KAczYcykAOGXUteMXl7JMl2hTB5Jym9iMejptvSTeB0PHgtyKUDzxv5c+oR1/RJ974IzJHkRTXRJyR0V1481b4psAmpSs68orI94P/lKwg0ShcHqgyUDlKda688lHQeVJO3VG9j9rhBPuDyBUUv40jbks8vumAoyq9F0nRCKa/ps7ckmrzVa2ZbcwIaoSSFUrH+iL7ji5qs/Y7ps1T/YXE/uJBbKmmqvry3Nm2QrdwZcYUyw6AcxHwZkTxcpvwhIlUqCeVG6ZeICpZq8qVADCJAqEQSSJlC4qOavEWUt0xvo6b60dMWYS1pOjbqKz0BRGZQQayXxIjMpVQNB0s96iZvMlPj7wHFnOpFIEnt1LHnz374pLZjhI+DfvND2TfWPeGslOO8ZlGd5LkolHicOonrI1VIUigpgKZaC5yi64wkD/+mtnF9VQ3VK+uoy7FpVSGlvpyxSAY6yfRH4viwzKS8H76qs+6NCZh0XVZGUkuBtkahTLPIT9fDqKmwJuFBm8Rz6Ylcj4pCiXBLieIF3R/R3plHH9QJjCYenVBSe8mSEsdcTN6qH5keHKC2ZytVNBLIiQHVSIyK9apkosHOd8gQAQK+UAQMNaBJnQRJFSS/VjWtEE6CqJrHokK5sSNbCaSsIRkllwkEvgzh+kggddKCwH3ZeVGluwUBFSXVb1KP8sYb2Os+ECZvJaDC4UOJI13QmTdQV+1TqWaify0Qowhxt344koMriayVKG+RKAUjtZsbLIWITNyiLy7Jxh3VagKJic3dCKVr37wUSu35y4BQOvDU39K3DqQcv3SFUquWZfdZCcoRuWwV31H8jm4zKpFWXGxEHkdUHHEdfJmX0fPiHtTdO4jk0QuLW81zNUewnkKLAh5Vv1gc44VC2VcqlLIIhN22JJSibKNM14ZjKqXssn0o2xCUIz9VMpG2QqmshCoQgtQsi0CaUCYVRCJW5UFrgkeoEcVx/zpr4T/XGnDGQJnYXPpQInlAtao2asgIY1OoiAQkCeoxUqLykBLlHXVRGimPJLWFvwkCawfdKEqlZgJXczC6EUo9d2dnwxGUoxFGPGwk63ge8dziMamHQ0nadUI5QAbZqCbvmHRDoNROIsel3BcSQtXkjaRTVUN1QlmkLMdlqkJJf9P9pd/DRD6/rreWjy+w/Clx/3ivkTLZoxVKMVisXQowaKTT5E0kzFYoXfygvKCrLyk8C21TDSkb2CcaVHVF0ZHyQ1cAlKooFOWt+3qpx0Bv4bQtzpmfv2qZsTHICPHfJwDuvzj1MbNC6U4oSaEkqH6LVNtbVFmRJnG8z6iEoD+JDyW5MYj1w87a8Xj/aj6Ujv27lf0T62kKpR6UI3woPa4zqatugRt4P2LVH6mmCreKhGjw1NOoEWqBmO3/m4K0qQFuCPu4DDCRGJBaSq4m6jr6eSEipZq8HZYCrTqWq3qqtamn/aG+/vYttApqFS/EP84HuOec1imUMQ8fygRCGU9zZl9T1dJBVZrUdh2KOI6p8iWECCXeg+RrjGMPutioAYrCZUdVKCOpFUoKwrGtPdKtgZ4z/I4v0FRVjI5dBOUErHP7yYtWwBsp/TSWpmXyNoX5kAiVnthcDcqh3H6poKpdNqFUqscg4UwweSsKZdhFoURCgOrgd/VWP5Akkg+laB/rBWjqFyUe1xXKQVItVcmLGq1Ny+pcCKXaR/V80Xb0u27yxnKH3QkJJm9NgVSDdNyW42/kW3rRUuvYKAq/Wh4rkjxcF68Dnn+8ppZCaS0nv1m1whCeXzUZOeaUJFi5Q63rju0d0S+eKYAIo6r8Rh0+lNZv6E5BabBwP0go6V4T++jRPpQ4WGC6FkzEq5q87eXKoJpO4ADCNjXqA7eRWqFE4KBKSqE6KerpSIRCqZuwZeQhlRtLUDA90pnQBIcDOAba0HHj/jBIKRW49GICYmjypoANAua3c2QBkIFTOMGiWZtqfZN5Nar4UKoEz/b9o3yLSgJvMoPLa20HXtALi2rypt+pLZUoudWrT/bioJJllShSbXrbh1Ixedt9SxXlbblh2L56brOu47xKsqL2DYH5OPFlSxDxFus86iqh7bLiolDiNTG1oByhUGrPIQIzKLzxoLNtPT0Xrbt2GcALtwG89xS0C9CUTBH/mSqUdE3sdGcasabzha4ZpFCicqy6UIjIa92CorgVCP/heKS0IPm2Qilfpugl3r7mcrxSFUr1WpEfOJnQ1STveiooNShHvAxpfrC2yTsYJ7h4vHa5VIX8pgARLUpVY/tQKgRJVa8yDspBghCLK5RC+cPvUnG0A10UM7KqUFJycFSnWhRCh/W0MQ6YSCMSVqrCQmoXkVFdoSSCaJEXd4Uy5qJQqsnL6ZOape1CHoSyK7A6iUFBN3k7FEqNQOoKpl5G8pMaQ9w/aPJG1Ctpg0Q5TJv0W3XCqW1UnfV9q/vCQKvpMrJf3Tcux/v28mGmTRJJLVWVYDcfSjRxY6lHa19Wv1XTec/OQ4mDHA6+mKMvqCiUoD/12qSRtE2NSKbyodQJJQ5WnibvJNGjYkKXE7heN5ra1UvA6RNcq8EKpbtCqVyzX2ZaFVl0NQsJIZJF/EfRqlRnGgmlCBYJOk2BdqCVnBhtP1kl959O2vQqSLq7QwofShHlneylyo1QUnk6vJ+pNKhr2qA0ZoeUCmWSe12t/ESVdERUN1bG0QJjdPJnE0qppKFC6XAVCLkrlC/cDjD3C+dvuhpqjxUmwKI5naP0p7K00LHRfeSlUKKrkGrydvNBVY9HvNBQmioZkIb3pK1QSh9xJeG57Rerpm5z5KF0uXdtJVnLi6qa48V3SSht8upS3Uj1yUVVW/WhJAUzBYhotXgolGpQjro8GfQADiSFlP/RSj5uKZTYFgW6lOsKpT9RoUTyYUVTW4TRUiit5dg+KWekjhEZRZJA5lZalkqhRFMvKZSkkkVV4uhRhzuuUHa9eLHTTz7Y7xd3uqNHeXv5UIrlmo+lUBmV7y3yOvSxKwTFTd5qiUkk/boPpWryFv2KxXN7onI+WUsUoRJKfBmZ12TVGidSqAY/0fXGbcifE/e9WPr14jXE/at15ntuLW8EDnjoz4OmDDR/CYWyUVlOd7f0TUsHugKwcoH1ufw319Vt85k6ydq+X6pCqVXc0H3g3Hwo9YnOw4fSEbXaGlDaIPahtIFKCZq8jQ2rAWa+CfDuk9YC9cXE1S3B+RJhK5QOQqlGMyvBJ3hNKbWUnpqH2lV9KEVHFT9G1TewVQqlIj9Qm6gIBnMsX1K6t3VzfBpBOUaoGWLqcSfsX3s29EhreUzCh5JcEYTp1cX070YoMUCDgkdUJATluJBdnVBmQqTbHSkYC/WJXgCor+RXTUo5Ekp0t7B9KLWXCf1FWTfL0zWSJmpRgUgQRiUyH9fRySqSQD0Sn168HL6uikuP+vJMAYtUFYqqjjmqG8m27fRtqFA2KAqlfG6FyTv5mBf0UCht/7NY2xRKMnmiOkXfayMG9PGbNtnAT1Qw3RRKIiNkHiUih8nMY+ryQKJCSYSQgniIfFKAhlhfnh+68mSOxf9tQonqaYxqfVu/UV+JTND5o/7pQTkqvnYpENURWBEyRHUdN6jnGv05HdcMMlMom2WwEkXDkyKJJE4olNH4NaQobzsoR4swV03gZCZXzdj0EiDyiJoAT1dY14SUdlSVbfcN7VhxP+hrv4TS67rk/Az25KAcMcghoaQ6yWj+Vk0lNDEiGXBLEuwGfbJAk/FNJ3iubjv4qwNwIA2Tt5p7jfYnJnDMSqsk3/XaXq0x3FZCGT+admon+4HExUeT5McvKAviycYTAq1EYIvy+EQjMigHTW/BxBreglC2xJWTZAplgjrmct+pJNKtUo6ZpkKp+gWTQolVWTCXJCmE6r7TifLGtC70XLgRSgdRV54NlehiYA69bNmql0df6LqQMqdGI+vHrT9nbudGbZPOczrH3VHwCgCia0x+pqRU03lypKiy0qqJ66Keb8prKrZDicLlhZjSmIkXJZmejfJKJlxDRVV3ZAnwCMpRTejkM6lfI7QM4LrkO6+MgUKBFoRS6Ytq8lZfzul+8gD5jNmmXjrNirqj3gXtoVCSKZnKDyJxE/WxyVghCQISAyQA2DckJzWopyiEUVUkaV9quhvb5C0VSiSfSGJI/VQjjPV8lHha0BxOplw1gbmryVsjmkRe9/nZ5/DfzP/Kl9Y57GjoQUTJTd4GBJUXPf28NyOhVE3eig+lZfK2fseXBkxyTucKCSYmslfvLzWVEzaH1woJJbVNAUIi7ZBh7dt6CbAaxbbxuuO+yIfSzu8pP7+si6+vVyXK6dGEEge5eulrhPVkkUyqygYNrliGK13oikcKxBVKZSKzfShdzDD2fjS/TjeFUlfDbFMkbicdz6mttoBGR+aTNjCZuGviaNutwZd4jfB6KyogmldxHeEX9n8XuCTkpuTOqsm7SSOUij8s7UP9XSeBXlHelOif8OnLACO3ABgpK5qoQRgqmRBBOVYGBUEodbKh9iEZ1Be6ZKSN+uJmepUKpSPRdYKpVjsf9OJGRMXNZJyuQkl+rfIlUvgsdxW8XiKp//RiQi8W9DupxFT8IBoVpRdtBTNB8VWUS4dCqURKm6ZMexZx5g518y9HVVmvMKSavIVCKV/W6B5Wxz7aNymUwh2j3j2jhm1eR0VbSSenElT1BckFNFFviABsko7JGzJXKHGCL1FN3kRi5DpIMLEfNOETuQkrn0hORFQ2XWY8hVjxRZIG2k5VznSFkpS1uMk7vr2byZvawLRBOilB0yyCLqGaEB0U5fRDLQUQkaWuBpWN1NMfeZm8rRNiJgQngVT5LIVSfIVGeYxk8iaF0nZLUFRliwwaYh9o4lZTGOFLAL44UGCXej+qidH1MpJIYEtVhZLeQeXnp7UGbDPbJ5Loby+0D6sBvPfRb7PnEkqc8OulQomgesb28la86uiKRwoYbkmO1XQndruaSVIfJGnAVvzvEhVKTT1tL4XSrpTTPR7mbgGdgKlQiZSeCsqxXsSaaHHSGjQqvq0alKOny9GCchJInmL+dS5XfNyo/47jMQRBto8Ic1pi/kMilLg/XQ0lE7f0U7Ojmm2ym4kPpRYtnzLKWyGI1C/hQ0k11fUgHA9TLZGHwZvEt02276RR3tLFpGoNDHj3Edj401cO9aDT8Pl/ABb+kHwduo8oktkmlIVOBRMVStsMnUTxdTV5S0IZi8UJpcPkrfv5yvFNV+FVFwe83zDlln5NEhRKqdAiScSyjwmEUjV5u/mrk0KJbMg7Ty9VI1lPoj04P3VzZ3rqmuEgUI0xU1ScEV1FfzuZ2ofaJcVSj6DWP1s08qATSKo5TaAUQqRQki8gVmHx9KGU7ZGZFfs2Os8K/FCX6wqlHqzTHYJyUkENMtLTBukqs8qz3BTKMJY3lEMyksQWSdzRp1FVKFX/S3JjoH0EtWuCBLNA1AZX+izvR0r1g/smokjmeyKwtJmdfF7p8xxZE71FuaHxmvX8tEE4UZGqoxPK1gSbtFqhdAnKcZjfNYXSLbG5eCuXJm89kblKMPWBus0m725gY+hmQH9ST4XSJTrV1Y0BA0DES4ISJofKEAXlULUQaguvg61QOn3a7BcXuqds5ckjKCeBULoQZD0lkZuvoE0QLIXSuVwjoCnSBqnnJQGO86acR0F0TReTt65QaoEy6jOCxGKrXePKlw79xS6NMaFw2c9xgt3Z+OwVux54AkghJB9Kug/oXl48x/okVyH5whN/WdDvAXp5Ukov0nIcbymIhnwe7UpeCklMRVaV6ynUfBGNr6VF0wlmWCGUmsnboZ7S+g5rj6ZQJgFVjVkXlpWaSKFU/M5UcpEpTyKFktSriOK3RiSGCAD53rkplG7KWMyF+Kjf1aAckVRbUTsRlhrmrlBijkK1b7bJ28OH0ibDafhQdheoim8yhdLNh9IRlBNzBr7gnYrL7bRBDtIfryOO14TIoKMmuqpQ+p0KpSDBmNpYnni8l4i80zWg605cka6xW0lL1YcS2+n5PpQIjPTOHZo4sKSZ0NsBfVJNAde0QXYkotoXrQIHBTmo+yXy4Zk2SHOct8kG+1C2P+ImjASok6+u2qhEjlKxqKUXkVCqPpP6/ePpQxnWFEpSNVVfw4h3pRxU94gQfPWWs217exeFUqo8ouKP/kKTSXAKVW+i86IjIdhJIYwqoSQTpVcic5286KQv1naTd7dG1VrrkyLU6byTQvzLV9Y/gv5y6nk+dVJGteOtjMy2QklQ7xc3kq/uQ420twkqfldN3hohtAkl5iLV/dG1vuoKpcOHMvl0118mo96gKZTUOqpEbSGUSA4wjQym+RHtKqSQiAORNjIT2wRS8/PTFUr0kdN9KNXvZPJG8ygplKJqihLlTWeN+kKVUrCetNin5jupE0cypDTLROBZpVAq5ytV2qBAgjKsJhA3LEJpBztZCiUF4dD1tbdVyaj20uBQKGVQzjKpNNNyta/NMQOa5MWzzz3pUPL5ot91f0n9N9yulxDKjQD9h7qnj8gU+gSfAq5pg3CQEoqMdFanN3gVuDwhDZBSelFXvyh3mnrcul9da8FR3okQCqUHoVRzHqpkRFZ0UdcTEy35biHQl0sPbHAQyibnNVajuGkfsn8J7g8OhVL3oZSDjhpg5qVQqiZ9UrzQh1KvXa2TkHYzeaspZdAvNT47YTon61hdnrtkwUtJ9638lpB/Vh4fjjGftaL2dmcDX1jUa/zDRxb5Wvqz+/qporvVROn6/aKq5TqhFOOXB1nV9xVqEfWkbVWR/GTVPprqWKoEZWGAW0Ld8STWHf17ivKLmK4HzZI06dKI8EyFAVcOM+HXRmcEcKYBJWpQBgLJgGqiVMkXfXoplNhHVWXCM6KavHU1NR6UY1XWIYWSEllje4ainCF+abLM2w+ujaeWUftgpS0ybSKk56EkZAOhxD67+VDiuVAjr/EcqMEqOnGndSjYSb1ORCCR84lroFx/N99TlVBic2jaRkJK2+sqNG6fSqG0XwbMFIRSO86eRyjpjKBCidAVStXknHabrTR5k5O7HiRBJFGfdF0VSr1SjrJcrVesk4w0++oNNnnrsAmYG1TFRTd5q8ogpkOhSZDQohErfQKnQA877YuZGGTiiN5VzYaR5CZv/aVGJcxqUI6dsBzvR9kO+lDq9xv6riH0SkAucJawTGHyFoRAVShlf0QGBCuXpGO5ur1OYmRqHLsfbi9fqRRKxD/Og6wEHtucT5Ms91IRXRTKhBys8fEV81Aawpjn4v7hRVZtN46W+Mu5GpRDz5/aJ7tuuMe+0i1zS8v12uMuJm8kUPQYkpq0oNmA4EwsB2rYJfVE05AZhM+kRij14BvL1G1CUzQzH0q1jJ9oTyNGalCOrVAqQTnY3oaIT0T93rDKYhKVEQMGz/J7KmhEWqht3YeS6n6TC0FWmrxTuBLovquQsH5cObZ+txRLJJxUnYag+806KuX4TGHyVstYCsKpqKO4jF5YaD3dh1KP0E9GKHt0Hkrbx23ed4k1uxHppgpqi0JJExBVttAVEnVyTkko5YBJJm+9D7baYiQ362UKJYqWkYZCqU6Q+sSlkjoMytGvoapQuvnFLvkJ4NEr41VXEhKbe/lQapOsm0Kpu4AkmLy1FxaH+uriQ1m9IZ5hIRVSuaLo97DqQmJP/v64yVtViR2f2kyGEcBe/dD35daPno4ENxoPP0cxfsmUWbRcTdWTrBJYgjIZ9SaUqsk7mcncEeCo+y7rvs16lLhiQj/9lqSnZ2KBCeuweS1ARg1ibKtCqQfO2KoUOAlAXKF07lcNqnAqlE71lAhjAqGUQTkUtKPmoUSz6F6/BmGuDNLQkUB4SOPRHkNab4B891zhHQfV/YNyUvhQ4lHrCmXYg4DqvqlCoXSYrJ3bOyvlWGqyqnCjqb1F255M3LWaL65aelHtgxehREKKLh49V6GkwQ0jHh+9AqBS+g8RkkTveSJD1S9GpcQofZG+vZ7exYvskl+Pl8lbbVsnfm2t0MG1vB2wXhp9aZi8NR/KhDyUWj1k1aSNv1MCZvFduV/WL4+vr/s1Jpi8FUU8SVCOqCeu+9p6+VC6pAMyZNogRx9qKqxPrFSVCqncMhLudcXkapsnA1Zic4ePpUaAiHBThC9ZDux2re38n/8nHqGdjkLZQ4Fqr+lK2vSAGuXe8PucfozqeukolLrLhE0ow/HSi+p1d/OL1S0DSU3eKRRMD4zLM2HvMoDjFxiwaW4ioSSo5s907x7KJakSSPod/d7obzeTt5dCiSl+HIRSRvXSvnQlTUQfx+Jpg8j8SlV3cNtUSPDx0xVKrdLQQOlOvrIVxsPOhmpeVs9FKCWhTDR5h6UrAF0TKx1TPJJfNW3jPzJh62q1W9ogJIy0O7drnGDypscJnG27+lAqbeGLDaXR6pEKpWPwX78iccJsjUKZocnbLidHCqVXKh99okoIFpBRlKhO2oEHumqjfbcjONuHEHLaIAKdBy+FUiEx+sSmKCdW9RBl+VPXxdO1JBAhD8IlSZ/tWmETSiXVELWTzIdSpP7R7mm9tJ6uUDqStis+lEQk1Byw7U4oFUIj/0ayIY7DTdmlY2uUBJJe9HRCKfvh//I1K1paP87eqlB6pV3yeiFW/RhdFUq3rBSRNBVKNHkrKqId0a9sr9d6V/YtXgS9/Dld1odCzMqXCJo8ZzcYtv9bTSRxjGyNQqkqVA6ztKJQkYKUyocy4mXylp+q2VZXynB9O20QVVnxAdSk+RhQ5ZyIlp+SiLce5U0VfmplPetsMXmrQLLsLIfo/O7mMxrW1OQEdwX7muP/VsJ4tR2nkmm9JKgKpZpo31GlR7hUuL+gRD0CqpIplD3bhzJVFHdrFEo94CUFYhS0QL5vug8lTfxelS0SkvHmpW/yJtLQmmh2FZzY3Al5Xr1N3sokq5vStInMkVqmtsqbSHopJp5BOTRUK35myWp5o/Kjpu4R/dcUSt09w1HzGn0oNRUQ941lKRf+CCmRKhOB18uT8NWLxMsnUuk9jYzY5wHrrSPoRS9BoXR5rtXjbM2Y0RNN3gkvH1rYrhqUQ64/Ue1+0oNx9Hr0dmlczYcSI7fVyjzkJuJ2T4jfNYWS9u8weWsKpbp+WXlcEFBAqVdalAhdUt5UtCbKGydxJFduqX5aNJ83mtQTorzpk06jS81p8emRh5KCQ1SFktpKn1A6+0KEw8pxGSeUpPBhuqHNpPEgm0zeKvAeUJPZh5MolEukppVQSUgnipqbg7jnXFRDdTtMXI4maCSIpkefcfsmrW1doYxH3hspfCgNO7F5nmFCqEcrlG5ozeRAJss0CaWfBiKsjatuZ1d+8KdPKM00Td4UidrOCiUzSnBGu6c6r/o10oMFRI3iqLvfbIJ/WSS5j65ey5ukADW1iuqfmaBQBhMDUrxM3m6qlPCh1EgtAstSrpzv2nfHcWSqUNpR2orpk1RHNRiK0uLQMlFSENmAu8k7ZT9aY9XIZujuDbpvKk1V9lir3G96aVmviPqEQEXtpUhRKGObTADYbDJAv8HxlyIKZFOflWRBOeq+6W89i4BOKF2QR7tXAlXcTN5Ilux3zDSHYtU3zzYbx5zqFJFXatJO96KbQR2kJG72Rh9KtU9IalQrFPnbWQql6VAw1dyGyaCnDSJCWe/hnbXTTz4Y+312UAw1bZAKvba3TuQR9P3XpuR5OnWFUiemFJFNw338vjGg1G99wUT4pDrqfaY64mrb8e9OX1y3lyW1LVRCURXFULSqbdPPLNOmq332SX+A1T++AX+95BT7t9ycINw44wyY+/EzsODLF+Dh22ZA/75lju2GDiqHp+69GhbNfAnmfPg0XHXBSeBHX51kSKXMtYZoYT3w+d9Z1SjSQL+Z/4HAMzd4+wvRoJgi4tyKXJWVSXCgVcmKTjpIadJTx7QW8jyyyVtTKFNFv+tKB0InmHqQmKdC6TGCe/pQyvuKLhkuX/YrwIt3ACyZay3HZN6l/cViE9W9BEKpSisuQTkOMowBb7pCmQFSbaMrtA7zZsTpF6mmDaJngZYRoSSCiS4Gd56htMuE0gEqJ6krlXR+6RZRI+1dCKVw79BVzVRR3mpbpFD2G2L9VtLPqr/uUChd/Grpd8/7Bz81Ezgei8p0qNCABiJHOCkXycnbS7mL+9qlB1VltEmCXEYmbztVEYnvUkHy8qHUSQ0RU9W/Tu8Dks8cVaE0vYlzOgolqbq0vU5SMEp8cUt2zDNIvBo8TfMqMU8kgqQKvlaV3jXTzyPF0WOOUgQxIbsUJgD8vo+18ppw/HzrirfqQ0l9tNMG2W3GjzfZcWKWAVEjPEOG2GpCOWnLMXDcH/aFn+c5qzhce/EpsPeu28Hpl9wCh508AwaW94VH75gR36HPJ8hkTjAAB594CZx31V1wxEHT4ZIzj02+w7aaet2Ag9/LdwNUr09rdV8kBL5VC+M/6E7t9lt4igmVItSp0oRKRnSzKCmvNCC32eQtP7PjOe8EpFAojWQTmVMJcZQrVE21Xj5rOvTE5tQeXfsi+WKGSjmui+ZnDPzBCfOAUwCOuNhqBidnndQl5KHUTN0KycCMCvaxtCbvaapt9OhiR5S39KGkJOtqUA49C+R6QiZvckHBa0gpmNR2vdDbAtT0NEvkKkDEPJlLgl7u0Et118dE3Xoj13dkRPjo+Xg6KgpkU/el7ls3aav7tpVurf8b1wO8/oD1AkEvHxowP6Nu8vYiWjRZZ2Ly9kpkTkE59DvdkdQ2raf7UtL6tt+iJB9xQukc4EMuPpRELmrSVCh1pY3OGRHJ3/0ahIvXFEM24uJlPrhieepJ0S0oZ1mLAeN+8MGj6yUBVBREL/9XldRhQA6CyCCRuHjdbxO2KLA2/qUxfl8mKJRKWipdoaT7iNwcqIa8FyhtUKZ+lK0ilAX5efCPGy+CS667F2rq4mam4qICOPrQveHa2x+BL76dAz/9ugguvOZu2HbyFrDNxHFind2mbQ1jNx0OZ19+hyCjH33xHdx637/gxCMOgCAqK17INEdDZ8AryCKVQoOEQBBKMutFvJM0k4oiB1qDqqu0GswoHZAvAZ4+lLbZz8XPVVU1Q81xEkZKmpdq46WM6WmD1ITVCFJ0MCjN3saME06ZVF0QyqRR3mpQjmbytkmy0XGE0rMWN77+y79zC+IvZ7Z/nU4o5djzwu0Az9yUeT96G3TyV1DkzDGaYPIGDx9KheS5VVxC2MnoKZdqwJ1QLv/NquakE0pyR8JnxeG7rFTlsX9L44Xt5y8BmhriL/Ea8oz0TN6i+QxN3iqhIDKhp9jRCaG+rf7ZrJlHm7XtE/z8MIhH1me2osDjptyaNINm4n21Pols0HlCNfK1OvlsZhmwGtCSNNRUVA11Uo9YJKoJGUl9KO2yh0T25O94PVTXgT5aTXkV1VHDJvBUetEtsbkzr2miQkn78gIlNs+0nnergnJuvPwM+OCzWfDZ17PhvFOPtH/favxmkBMMit8JC5euhJWr18OUSZvD9z/Ng6lbbQ6/LVwGG6poEAP4+Msf4JYrz4Jxo0fA3HmLXfcZ9BlguFQ6oGEuJ0kVhKBcRp+tgVsbETMmLhSasPF36ksQcxIq36lv9neRUiAGMTm4BUw0QJtWquBoWKyP7UZkkmhs2/z1a4iZMchZOheguLjVx2L6fHZK4oBesi8D0LbZ3kY0QOfRdD2nmJMXn8EAetP44umcE64pumzYk2mLWB41TeEkj6UMsW285vjdF2qGgMu+zKIysTy4YaVVxxpx60nWp3o/RVpsxScCJpgBvKMs8z3upyUQAH804tgH+opS3/HN0/QZ4v5CHxlcD/creh+z7mUyEwZiEfBleK/hudLPk+M47Xs9Ipabcn1URgNymS+/SPQH92+aUfG3PxoCP/Z17hcQ3XQrCIabrTEB80+umm+fE/s5lCRav67pjBkdPXZ0RRv2/YfnGe+nfEtNCjbWivMYxupEcoLDax5SrqfPZ9jf0dc3YMYss61pynvd2XYkFhVjmC8Wtb4HsBVrrBPjmSSavtpKsTwcCIp9B9F/F/ctS5gGwi3Ovoik6laNZDofMepLzLqfYpiixeUahyIt4MvNs58L9ZwWBuQT4PNDjWCMGIjghxySj9TzKENf0NqWznWJyPUNnx9iBp6FqFClsG8USI5kA79bBDEKOT6fGFPwWbFS0FjLI+IFMAZNJi73g9+I2kon9oGSUYfA2p7CdMS4b5pQ4DOESok+lxbpMKFebpv6OKy+1Ud99nOL24fleeou93l7tEHnLd5GVCR9F9dIKLMx4RLhNobERDALnhcyWVvXAe9c6/60zluLvIYBeQ1b5DUr9lvfq2N+xzF8XW9tXy/zxGJaNYsf0jgXAJ/YN+7BWrdFjIExcf+I507sKwrNct9ex419CxpRKBTzY6zjCOUhv9sFJm4+GvY/9sKEZQP694GWUBhq62S6FImKqmoY0M8y15X3L4OKyjiZRBC5LO/fB2Ce+37LCwrA55JpkwzuQ8ucfppuGFDcdjlebaMyEAAMzynwGzCgrMzuy+CCPPAbZVD72Yvie4ns2xKljcpgAOqDeeJS9cvPg9yiQsCMhIFYVBxLqKAAVmHqBYjBQDq2tfMFmWzLsUTyi2GFJBhl+W1/myzN8jbCQWlaNU3Xc1pRvQ7qB4yA/vl5kK9c46Eu17RZEspgNCyW1+bmQCVOamYMhpSVQV1uEDA9eKERg/4u9+uGwhIxUQ6sXAF+l+WN/30YIgWl9v2EWB8MQDivQEy4Pp9f9GO5PwhFfh/0UdYLFxXBSvn3sLIyaC4ugTVoRQ/mQL+yMqjPz4MKSQiwjfWSUPbLzYGCNJ4tFfh6tFQ7T47lhk8s95sxsZz6VuD3Q//iQliGf5eUAYbA9c0JQnNBAWB9rL5BPxRhe/gcPHQBQKl7Chj7mhTkC2VWv66ZjBkdNXZ0RRvrfAagfSMfz3NZGSwtKBIT0tAAgFFWBsuK+4rvAyACucq9judR/Y4vHX3ycsX9gxQUz2NNTo64RgUBP5SXlcHGYABwVMf7EO+vah/ARmwrNwC5eH9JlbQ42gJ9y8pgRU6uICyD83LE2LksJ0eMjQNy/M6+5AYgIMdKOh/NBfmiL0g2sS94v+B3/RqvikUht7DY8exNzgvDiYNjMKspH1pi9TC0rA9cWxmD1xvDMKTM3TxuGvikmFCaXwADIvmpr4sPz0wEyktKoSgfn/AakUQc+1aQh09uCPyBIAwtK4GlBn6vhrqcEhhaFoD8XJxLGyAQyIGhZaWQE8SnogWCeQUwtAz3vd5WKLEPxX5L4Q3kF8NQX9BeXlZYDKavHsry/FCaE4HVsQAEhK9oC8SCeTCguCjlceTJvkQCuTC0rBhurIrCnEgLlJYUQGk3us/bp431jjamL4nAuogfhpYZUOzDO3MDNJl+1zEkLxctJ41gGhZh8wnLaxRygngNS6AgiE9CGHLzCmFoWR4EDGtfRYWlMDQXt7G+5xaWwQBBSq1revzq/mL/EZ91D/QvLpEKpFV0AvuCr2WLQ1XwVB3eP0F5f1ULmojH0qcA26qDPPv+cT/u3LwCyPHVwYhSPH5ZnbC9CeWQgf3huktPhaPOuFoQx85ERV0tRFT/KA2rqp0kVQUyczFJ1tVBOI0kt+m2EWmy+tPU1OjY/5rKDWCgqWbm2+K75qEk2mhqaoKYNPNU1taAUWVdtGioRbRl+iyi09xY72i7rcdihuImzZqmJoi0MsgHFUEkcdneRiTHjkRwPafm6w+Cf8ufoHLejw6/L/Wa+GZ/IrYtLZf3RXOTWB6tt7IBhELN1vc6605oaKiHFpf7NfDhv2HQktlQuWGt+7Wt/jLhfoq0tEBMmhPx6LEfmL+xobEBGpV9mNH4yxj2JVZsvfTVNzdBM36vs/oai0REG6RQVtZshI1Jni03qG/Vbs8lnfFoOGTd67JvTXUbYXUlUnCABjkYb6zZCKG+lj61sXoj1GTQl4ramqTPSrIxo6PHjq5oI9piuQw0yfsTlW3E6irrnMewVjaet+ULRHJ7QsWG9WAo5wpN3lV11thnxqLyXrfuyka69xus7/WNDeL+Mj97DfzrV0PFgp+EMkJBPfW11dBUXQ0Reb3XbFhnRYALMpS474rKCqvWugSej5Zca3lE3k+xvGrXaxxubhT+bfTs4Tm9YWQIxuZG4avqiDAj4/r4Iv+LdaZcz2MEbd1+gMrGRlhfF0l5XRqHRAFyAZZX18AQaYsMxUyxr+HF1nNWEwqL7y9WA7yzNgj1McudoyrfarNWLg/3t+bdlXU458Qzm6AZVTy3EvM21sOqUFxd/WVjPdSVRSAaiUIgYEJFcwxiOGwUA6ysb4H1dWbK41ifa/2+ujFkn6cfxK0T6lb3eXu0QaA28FgJhdJ3tCoccx1DqvCa9QNojFj7rgtZ93pls3XeooMi8WtYE3d/WlxdCxuU3KdLq2scY+nKaivLzLLSiLhuVXW1orITgfoy4Ufcxhrf++bHHHNDY651rdY2OO8fHbgcUS/nsA4hlFttsRmU9+sD7z53V7yBgB922GZLOOnIA+GYM68WUd4lxYUOlbK8bxmsl6pkxYZq2HrCWEe7FAVesSE+UOgIR8LuN8dztwj/m1AaNw5un856abchfSVj4ZCj3XBzk2fwjL9+o2gjplRawYGQfJTMSNhqS/r2xVqaXPvc6mORN7n4MxaDiJpPrhXI9jbE5CDNra7nFL//+HG80oqEvd4tJ0EsFoMwVRQRpL3ZWi5rS5vUrgwq0e8XG411kL9qPlRlcm2RRNt+YYY4BqyUEws1Q9SRrDw+8oi2bdfJiPVd8d3FNoKSUEZEtHrrn5mkx1FbaS3HbAtvPwaxX78S/UFTeDSnwN5/VD4LEXzeMugLjRdez0omz0+7jx1d0IZPvhDhOY5gG9++CzBp94T2xPilfq9a56ykFItCNCQJZ8yU93bIeT/Rd7rX8R+6KkhPs1ypUEabG6z7VL5ch8lPNii/o9+jOrZiMnslxyqejwh9p7GTyHBMO1fhFvFshDBd27BxYC7/xU6n0j8QE4QynXNrJ4mOWmMG9cNr2xY5xiDBoHRAojQiBvLJ/TdH5XlEQqI00yxfkrENXI4uIYiaSHx9az3r2SesC2F/4uRkZXMUmmOmSBmECbLrIwAD5ey/OpTecTTI8bUyHANbl+iG93l7tIER279FCyAclfeUCnk9Zze43y/N9jVzXv86ec3IUF0TwfMYd3atCkdFeieC3jZ9n7EMc14aMLchaiePd1sf8XOjCU9W+GBeSwDC0UbhqoJo1O4fHU3yWucKF40OIpToG7nH4Wc5frvzuvNh4ZKV8M/HX4LV6zZAKByGnbebBG9/YKkpo0cOhWFDBsB3s38T32fN+Q3OPeX/oF+fUqjcaDHuXadNFgR0/mKlDJ0OL/Vp6c/QZfCKhPUgk8F/ngdDpHkmIeqW1C8KuKAqIIvntnOnTWf+xd6OlEE5KaBNtI5oZDsSVk9Y3o61yAShlGl0pA+cUJ6SpQ1yZA3wCsqhjAUdZIl46S6AVQvi32d/HP8bnwUZYCTIARIA0ccOyPTQm6O8//eM9Y+w7BeA8mGJ2yVUzlEC1OwsAVohhpRVoSiyQZLXJT8DbLF9fDllzNCDEDGtkFt/xD49SnTa27ZYgZDHzAAYMhrMx66CsDSeDw661zdOGpST3up20ErUJWUMfa5FZ20X6NHdeu5HAgXlEPQUPlSqEQkIEkoMuugftBpdqyiZ6SBVQEdPwNEL0QUB040nKpB4Lvf62QdfaXUUCAl5KGPuQTh66h61Yg6lZHIDJpK/fbWszZ0iMgxfNP68BE3zPmcC/1RpvQWxNe2MBx1CKBsam2DeIifpa2xqho01tfbvz736Plx70clQXVMHdQ2NcMNlp8Os2b+KgBzEJzN/gPmLV8C9N1wI19/1uFA8/3LWcfDEC29BKBzp3LRBbQVWQ0GkSc6Mhtq4H6hezQGP78lr44SyfiPA30/mSNUORpxYtz2LQGKUN0XVRp2Rq+15TbHtHOnrhcfitQ+3yF0EuZFoSa/t+ak9ya+KBd97L8O+UZR3RCGUbVQsbGBhghWpE7T3OKRIrA/P3pw8+8O65QADR8hKORqhpGtDz1OKnKsYUOAglG8+CPD+04kr6vexW0q2hGwBWtS33VYIoKBYkEmBvHw78nZwjplykiXQajGNxHnh5EU+OLKfKSb3FkmkiWzMajDgvNUl8Pg6PA+JHYhHYoODEBA5IVCUeByJfcN1ynymKC2JhLKfrVCmdRh2JDzlXezN+LjW+9qHdUKppfChOC/9GtI12+R7X9rpeqIZkny1IpQbkNRi2iLqM5Uh7bLSi9fe9giYpgkP3z5DmL8//vJ7mHHj/fZyNA+ecO51cPMVZ8IbT94mCOmLb3wIf79PeVPOlpxx6yW57jMw823VgZIGvtVahHtHkEm79CIrlGmVXswEtkLZnJgOB0GpUdqVUMoSdqTqyH14VsqhT0zX8vZjAD995uwT/k5ttXdf00U0AqaqUNqWgHYit3efDb0SlLIniS+648XqzYfj9egp9Q4SSlQCSQ2k58azeo37cyXqtKuEEtenCmSZwlZDPYglAV/0SpVKOYFcWwEcnJNY+s4LOZ6EwB3rwgbcs5YUJdkV+7QY8HZ9HkRM91Ri1L9VlDHLS6FMoy9UelEolFFUKMFOlp0OyLxKSdcZ7gjHnLXgiWA2plAoCes91Gp3WOuqvpTJ8M5GA64cZsJcjyHg7MUGXDDEtO+7Iukv2mmE8g+nXO74jsE6l9/0gPjnhVVrKuD4s/+a/k5kqohuh4qVzrx4mUBNJpxm6cd2gZwAuFIOIc3Si+m0pCejVxN2I2QQRLuSNFW1Q3JMpDUhDyW9Jte6m5lXL7LyOS6eY5nD7cpMXWDfwvODCiUScdz/V29apk/sI6P1IDcHvea5F+hlg/D12xBc8D34DaX8oZ6HEtK8bygvpVpCtLWwFcpwaoWytF/8e1AhlMF46bx0iVW6FWZU2KUXzcz2tVoeGhm4Upm8vfZdHLAUMmHyDsTN4zlpKFFqeUqGN8JanklCgslbfv+6DmD7JAHpN1cUwbI675vz3CUGvFud3nyOqYcCM70v9hMVPniiAmB6qXUQlJO1yxTKDkF3NHfTxPfWI3FVJxOob+OdOml3Q6U3G0ovtsbkbZsY5f2LZA1fJPCzvRDTCaUHaaVnqL7Gu51F8fyxeasWQOOoiV1TnlD6UGL+ToNUym/+m/72SDzJrMmIg6oPpUsoXWDUVABgqpQEk7f8bqT3gmbnWdUr4xDmfGrV+U4Huslbr1BFoBc96kMwx57cC/3OJNEdRijJhzLNfQ2Q74frpJ+j7UOpbU+Sy0G/+qA0ED/3I77zKcEhABOl8N8YM+C6FQDnDcF10yMjP5O7q3dwMAPihLIpQZE0XAnl3r/4oCQJcXt0YwGsqkbrjPsNd99aX4cdQ48klBiB222BAx/hl5kAI7dMbztVKeoChZIr5cRzIlp/tAehjHgolHIgqK0EuNsZ1NbeCqVJ5fS0ydNeb/mvaTVb8vNnUDfrfxDW20kT+St+g5aKVRmkxFWASpPPD0a0lVWhnr4+XuqPYcO+N9pAKG3YhFIzeeuuNB6PVYLJWwe+qKfdFy0oR69VTqB7Gc34eYUQPfA0yP/ft3aa9HSDcqh6iB74kg70cnxpE8qw5kPpse93hFIVvwarlYAbtUwfkp1bVvvgltXp9/2lSh+M+M50tMlITSiDWmlF8qEkNwUk97Ssu4D6VtwTCWW39J90w2txX9GMFMrOJJQEHhNa50P5zI3OlwEVpESSqqebBTsCDoXSB6aM0jUqtZkCJ9tHr4y7aaSAmJa8Jvs0MOidB0VetFZ5Pcpr0abIe/zHpNKJXKlQYmWhNsK+Nnot+DR9s03b5N0OCrhdy1uvJ65Hect9oZUgDyN4rSIDhHR9KAltUijTvLUfXWfAgX1MWCS7TgqlSg7ThZKhptUEhslkaoSF+4Fp+5oSoaSXgGcrDLh6ePrKcFegpWcTym5G39sDqg9lZ5q8FR/K7ns7dyIyjfJO4t4gFEokj0TEvJSS9oQasevzgTlwBARqK93JIAWRdXcMHCk+ogUlmD+a0V5oT4USUVMJ8PGL7gplCmLZ/9PnYfXoKRBLVwG/91zvCRjHNJHKSE8bpD13mO8UQRHmSCjtIo3pK5QEVCgzrfiaqQ/lV/UGDJ4V7++FS30wY6go+JvZjpUa0QjKh8lof/g00m4TSvn9upUG/G1l95596eUqmSk+awll4ZKfWqd0dGeob8/0Zt0Z4ChvByg4qT3cKlC1Cbx4O0RWyvyKZE7vSIVSr+wzeFPIqVqtTJMMhmbyboPy7MB9F8T/1oNy4nt13TRYVwmBj19If1yvT1HVSOTylc8CPct6aqqqtdYnpaTCYBy/QigzjF7GpOhUUiDTifqVytaNv29uNODNjX5HVO7+fdLbdoDMO4nobibWnoQCUdIyfq11k3f7eOx3LOjFp8Qfj/juMYSy/JPnHKWPegwwuTOSjo7K9eeK7n4rZ3HaIHw7xeTQNLGREmJ2pEKpEcp+QyCw6IfsJpTP3AjGHkdCQcNG6d3GaA8EXvsnFG69m0dBwTZCz0NZuSaeu7IzIAilcrfcfpqjoo5Docy3zN2I2c1B2CwYFkE5nZGwG82heV/5Mpqkk+GBdT54bAMmrk69brky27fGZM7ILGirUSOU6QZ9dTcfykz63f7hQYz0gW/Q82d17j7J9YkN3k4VsSOIdp1MfL+oHaO6deh+YvlF4G/0iOTOFiz/DYL/uh4GfJQiNy0jI/jWL4e+X7/RMY3rCj+6V9x5RtpBYJnC99Vb0P/j5+I/iPKhEc1f0kzsIxJcJYH6H5b3gdc3WmNAdSeZga1yj50//t64Kj7dV2X1G2f3RoGdr9M90Xk2QDV5h3qaQsloT2TRXd2JlXLaS6F0oKEG4KYToEPh4p/p9woaYjA605UmaQL1tiHw6UtQXFYG9p2+dgnAhjTsWI9daX3ufbz9E/m2bezhJOu/1ZSDsHsHhGQ7nqowYFqxCf+t9kFZCcCMFX74qcGElVnkt0cmb1QoM/EtZkLZ28A+lBqy/DyQqREVGZlnMJDtCiUjC9HF4wom5W8lyNSdLqHc+2cfDMrJ5hfzLB/zujmqIgYcOd8POX4DyuT3O9ZklzG4RVEo082ZimBC2dtgR3kzBGyFMoscXNwUSlRDJaH0t7aEHYPRWtRWWQnlZ74J2QYaC6vTJJQfiTrOTMoYPRcxMASRREJZmYFyz4Sy14EVyo5KbN6lhBJTwcia8gHy3WQwOvM+fDKDcrpdjcevgUBeviNoolpWMmEwGADNWKrTn36tdwQTyt6GLOVN2VB6sUtAQTlYnlDC16lZAxiMLMTaJeDDxPdlZXFC2cN9KBmMTANzkFA2Z5BOK7sM+4x2AJdedCDN2sPdXqFUU6YwGIy0QYQy00o5DEZPRot8HjIJJmKFspdHN/d22InNs1ahjMYVyrcfg0C1TN7MYDDSwmd1BvxpQGamPQajN5i8Ecta0ucKTCh7I7I1AKUj0JFpgzoDVHoRFcrZH9tmPAaDkR6er/TDqxtMqM+wUg6D0RsUymUZEEo2efdGCO7Eg6dAtgflkEIZYXmFwWgtmEwyGE5QHe/lISaUjKQwQRRrYHRsYvPO9KFkQslgMBiMdsLwXOtzERadShNMKHsjBHliRilg+5JmeZQ3E0oGg8FgtDMWNLNCyUhFKDkoR6KnKJScKojBYDAY7YtQBuZMDsrppchS+tSBic2zNFCJfSgZDAaD0c54swqgXzCzbZhQ9kawybvnJDZnH0oGg8FgtDN+P8+KysmRwTnpgE3evRJZSp46Aj0lsTkTSgaDwWB0IZhQ9kYIgZIVyp6R2JyCctiHksFgMBhdByaUvRIxm0j1erBCyWAwGAxGm8GEsjeCXSjjkEE5WRvlHWoGqK8GqF7f1T1hMBgMRi8GB+X0SjCjTEhsns0m73vP7epeMBgMBqOXgxXK3giTw3J6jMmbwWAwGIxuACaUvRKsUMaR5Qolg8FgMBjdAEwoeyO4Uk7PSWzOYDAYDEY3ABPK3gjT7BQ9LppTAPOP+Ts0lw2BrkKoqB8s2/c8iAVy3FcgH0o2eTMYDAaD0Wowoeyt6ASFsqXPYPFZN3ISdBVqxkyDlr7DoLnPUPcVWKllMBgMBqPNYELZG9HOahzmtGwcuJnL7zIlTyv0UDRFUwR2W2BErfyModKB7vtBH0ozxh6lDAaDwWC0AUwoeyVSB+WEC/tAzGdllYrkFkKosK/nurWbToWV00+Hpv4jPSKoM+/dkoMvg1W7n2L/hn1YuedpEA3mp9x+w1a/g9U7HWd1QSb8Xr/d4VDrppRiH9nczWAwGAxGm8CEsjfCNCHm88cDUlyw5JDLYd0O/yf+3jB5f1i1xymC6LmphpGCUvlZBo0DR8PaHY60duOj9pMTtuaywdDUb0T8e/+RECnsA42DxzpIa+OgMY7fCFF/EML5Vh8QVRP2gnpJHg0l2KZu1DaJOzd87D/JYDAYDEYbwYSyV8KEZWN2hcW/O9/5q+ET6l40x1IBm/qPEp8tZYMhXFIOG8fvDguOvhUi+SWCWP6w88nQ1HcYxAK5Yr1QcT9Ys9NxgvwJ8kmBMCkIG/Zjxe/Osb839xsuPgP1VfZv0dxC8WlE4zWrN2y1L1SO3QXmbncsLDj4cte2Y4Gg/Xckr1h8hgvKIBrMk8fMCiWDwWAwGG0FV8rpjZD8qaV0oIiCzqmvFN8bho4X6h7+Q/iiYeFjGCoZIL5XTpguPjeO2xnK538G9WVDAbbcGyDSIn7H9Qys3IK78Ae9I6tRRRy/O/RZOQfpXcKy5r7DrDaU7TFiHBGTRFC0Ifvjcmjx75LsUp8QS35/BQRrK2CTN2+VZnkmlAwGg8FgtAWsUPZKxAnU0oMvi3/TeBWSw0hBCZjBXPCFm8GUZA6jpk3pX4kBLeGifuLP5v6jIFJYZiuKNqG0Td8WorkFsGHrA2DNNgc7fkczPLWvk0fsh/6bDiTIC4+80XGUKqk1FbUSFdf6IeOheuyObPJmMBgMBqMzCeUJ/7cf/O+Fe2De58+Lf68/+XfYY6cp9vLcnCDcOOMMmPvxM7Dgyxfg4dtmQP++FsEgDB1UDk/dezUsmvkSzPnwabjqgpPA72de26nQ+FPlpH0tc7AZdfxuxCIQk8pgwep5DuJGZm4kY6RghostYkmKoum3yFxMfhJCxdb6RsyZTBz9JpEAhkrKIX/dQjD9ATswKJpnEUoKyhHR2RrQNE8qpFgnkCPaC9ZVQun8LxL6sXr3P0G4uJxN3gwGg8FgtBEZMbk16zbAjfc8Cfsecz7sd8wF8MW3c+Dxu66AsaOtgIprLz4F9t51Ozj9klvgsJNnwMDyvvDoHTPiO/P5BJnMCQbg4BMvgfOuuguOOGg6XHLmsW09DkYm0AJrqracDqt2OymuOkqgf2HVFnuIv3Nr1tq/R/NLIFTUR/wdLigVxC1/3SLHtrHcAlsdVJVBBBJGhD/c5EjtUzdiK8tv0/BBwdqFVjs5liIZzbN8KGPSv3PZfhckHBb6dqrA3JN1m0yBnNr1EKyvEv1wDUTiKjkMBoPBYHQeoXz/02/hw8+/gyXL18Di5avhln88DQ2NzTBl4jgoLiqAow/dG669/RFBNH/6dRFceM3dsO3kLWCbiePE9rtN2xrGbjoczr78Dvh53hL46Ivv4Nb7/gUnHnEABAPsztlpyE1MvYMqY/3wCY7fWvqNgLpRW4u/c2rWiU9fyCKBdUOtdUPF/cVn/vpFCWZt8oHEIB9M+4PBMOo2pBiiOR1ROWk/WLXnqYJg5m9YJn6r3WQK1Gw6FaK5RdY2OXmCFIZk0nS3aHPCmp2Pt7ZBk30kDDH065QEVYXqq8lgMBgMBiNztJrFodp40N47QUF+Hsya8xtsNX4zyAkG4bOvZ9vrLFy6ElauXg9TJm0O3/80D6ZutTn8tnAZbKiqttf5+Msf4JYrz4Jxo0fA3HmLPfcX9Fv+da0BbcttWAhJUlW68ieoGTZR/I1+kqjmeaGgrkJ8+sItIoinZuRk26fR19IIhRtXQTwmGyBa3A82jt9N/F0/YpL4hxj36rVg5lvR1jEZuY2KpIq86jWQE7GI64atD3QsM3MKIFZqEVIdMY1QRuV+QsXlEDDDAOijKX9ztOkPdIvr0lPa6A594Da4jWxoozv0gdvgNpIBtwtFne5w7UYoN99sJLzx1N8hNycHGpqa4OQLb4AFi1fAhHGbQksoDLV1DY71K6qqYUA/S5kq718GFZVxMokgclnevw9A3E0vAQOKE4lApuA2LCyRn6MXfQHfS0KpY/j8T2HF2F3j+/OFATXI8ooFkNNSD8tk4AyitGY1lOYEYIWy/cZx8W0RA5f/AOtGbA2BIWPAXyAJZUEpVPcbmaAQltWtg34BH+ivF4FQEzQN3BRqAvuL7/l1FTDhm+fg2+nniu+1krTqMPx+KAn4YTVu08e9Yk5PubbdqY3u0Adug9vIhja6Qx+4DW7DC0sqrUww7U4oFy1dBXsfeZ4wcR+4105w93UXwGGnxP0kOwrr6+ognCZLdmPYeDK5DSeaalVN0Ynm5kbH9+raGhj3yjXgi4REUA6Ms3wrEf6KZRBebfk8EsJ5lomaUPLDW7Bh4FhYWzIUmnyWT2VjyQD4adofE/adu2gW1FeuSfgdzep1wybAhiFbClV01Nu3QYvPB1t98TjM2ekk1+MoXDMPBs5+CxoKLJ/PudMsMzgi0FAtotKL1s4X37v6uvSUNrpDH7gNbiMb2ugOfeA2uI1kyETZzJhQhiMRWLrCmuzRT3LylmPglGMOhtff/UxEeZcUFzpUyvK+ZbBeqpIVG6ph6wnOSicUBV6xYWPy/Uajacuu3EaaaKwBf2MNRAtKYfQLV8KiI663F4VkEnBCNBIBiEQA9+jbaPlTEnyNNWA2N8Lwd+91JCjP27AcmvvLCjgNNVC85DuoHL+7tU2o0Y4gVzHgm5chZ91isZ+BM5+HpvJRULvZ9mJZ0eLvBKFE+EONEI1aNbiLmpyqt4rSeV9AoGoNhILSvK4g0LARRr59B+TEWgCKi7rNdekpbXSHPnAb3EY2tNEd+sBtcBttRZvz9Rg+A3JygjDn14UQCodh5+3iZsfRI4fCsCED4LvZv4nv6GuJJvN+feK+brtOmywI6PzFy9vaFUaGQDI2/P37YMgnT4BPJidHDJr5b+j7y8fQb857rtv5YhHndxmoQ8E1OdVroWTRNzBg1qvQ/4c3RQog3Ff5D28JEocom/cFjHnteui7zlIHC1f+DEXLZkPZwq/sdkuXzIJB37wERctnQ+nCr6Bo5c+iXQvxVD/+SLx6DvZh7LOX2N8DTTWOSHIVRat/FZHmyauaMxgMBoPBaFeFcsY5J8CHX3wHq9ZWQFFBPhy6326w49SJcMyZ10BdfSM89+r7cO1FJ0N1TR3UNTTCDZedDrNm/yoCchCfzPwB5i9eAffecCFcf9fjUN6vD/zlrOPgiRfeglDYSVIYHYviavQoBMhpqBL/VJQs+U589p37PlRutU/KtvySUPoloQw0VsOgr18Uf+dVrYS+v35i19VGUlg9bmexTbC5DoItlprdZ97nULDOaTYnDPn8X/bfA795GWpHbwcFaxbYv2FFH4Ke+DzQaBFKNNWrGPjVC1CyZFbKY2MwGAwGg9HOhLJ/31K45/oLYED/vlBX3wC/zl8qyOSnX/0oll972yNgmiY8fPsMYf7++MvvYcaN99vbx2IxOOHc6+DmK86EN568DRqbmuHFNz6Ev9/3TCbdYLQRwXvOhsljh0AqN9tkyh0qfpREXFcoiWC6AXNC0vaiLyGnr2YqICkd9dpNEJTKo9ivkkeyZOHXjvX9LY2JCmUsCqWLv81ovwwGg8FgMNqJUF7013uTLsco78tvekD888KqNRVw/Nl/zWS3jHaG0dwA/ljbfCk2e/MWWHDIlY4E5agCDvriGShUqurowATjqpJYULfeJnnpQldUEZu+cwf4ajfYamXp/C+hBssqStO4EQk7SCmDwWAwGIz2A2cTZ9joN+ddW2VMBTRX5zZuhJaCPrZCiShZZqnVXihYu0D4ZpYumCm+D1j1E7RUV0BOBSUzah3yatdBJBoniui/OeC7/zjKSNrgUosMBoPBYLQrmFAybPSb+7+M1qc62yqhTAVUB/vNfd/64vcJs3rh+kXQ3h60hkYc/S0NgsTWjJnGCiWDwWAwGN0typvRe0G1v31tNJ93BpBg9p37gfWFFUoGg8FgMNoVTCgZSRGor4Kc6sQk44jRP78DeVVqfZzuDTs1EiuUDAaDwWC0K9jkzUiKTV+/yXPZgFVzwT//63Y3V3cUKHWQwQolg8FgMBjtClYoGb0G5DuJZRsZDAaDwWC0H1ihZPQqDJz5byhYv7iru8FgMBgMRo8CE0pGr0KprALEYDAYDAaj/cAmbwaDwWAwGAxGm8CEksFgMBgMBoPRJjChZDAYDAaDwWC0CUwoGQwGg8FgMBhtAhNKBoPBYDAYDEabwISSwWAwGAwGg9EmMKFkMBgMBoPBYLQJTCgZDAaDwWAwGG0CE0oGg8FgMBgMRptgwIApZtuaYDAYDAaDwWD0ZrBCyWAwGAwGg8FoE5hQMhgMBoPBYDDaBCaUDAaDwWAwGIw2gQklg8FgMBgMBqNNYELJaFes/vEN2HePHbq6GwxGtwc/KwxGeuBnJTvQ5YTyzuvOh8fuvKKru8HwAF+f7gW+Ht0XfG26F/h6dF/wtemZ6HJCyWAwGAwGg8HIbnQrQrn7jtvAfx6/BX797DmY+/Ez8OQ9V8PIYYPs5cOGDBDS9357ToMXH74BFs18Cd5//h6YstW4Lu13b8HXbz8Cpxx7sOO395+/Gy464+gu61NvBj8v3Rf8rHQv8LPSfcHPSs9BtyKUBfl58ODT/4H9jrkQjjz9SjBjMXj0jsvBMAzHepedfTw88NSrsPeR58Li5avgvpsvAb+/Wx0Kg9Hh4OeFwUgP/KwwGB2PAHQjvP3Bl47vF157j3ibHLvpcJi3aLn9Oz7wH3w2S/x92/3Pwiev3AebDB8CC5eu7PQ+MxhdBX5eGIz0wM8Kg9HLCOUmIwbDJX8+FraeOA76lpWAz2e9PQ4dXO546H9ZsNT+e31Flfjs17eUH3pGrwI/LwxGeuBnhcHoZYTyybuvhpVr1sMl190LayuqwOfzwccv/xNygkHHepFIxP6bCpHTAMHoOMRiZoKJKBDoVrdQrwI/L90X/Kx0L/Cz0n3Bz0rPQbdxDulTWgybbTIM7nr4efj8mzmwcMlKKCsu6upuMRRUbqyBgf372N+LCvNhxJCBXdqn3gp+Xro3+FnpPuBnpXuDn5Weg27zGlBdWw9VG2vhuMP3hfUbNsLQQeVw+Xl/7OpuMRR88c0cOOLg6fDeJ99AbV0DXHLmsRCNRbu6W70S/Lx0b/Cz0n3Az0r3Bj8rPQddrlD6DAMikSiYpgl/vuxW2Gr8aPjwpX/AtRefAn+78/Gu7l6vB10fxL2PvQhffTcXnrrnanj63mvgvx99BctWru3qLvYq8PPSfcHPSvcCPyvdF/ys9EwYMGAKuYp0CZ7557WwdMUauOLmB7uyGwwP8PXpXuDr0X3B16Z7ga9H9wVfm56JLlMoS4sLYa9dtoVpUyfCZ1/P7qpuMDzA16d7ga9H9wVfm+4Fvh7dF3xteja6zIfyjr+eB5O2HCOSzaLEzehe4OvTvcDXo/uCr033Al+P7gu+Nj0bXW7yZjAYDAaDwWBkN7o8KIfBYDAYDAaDkd1gQslgMBgMBoPB6P4+lGf/6Q+w//QdYbNRQ6G5JQSzZv8GN9z1BCxatspeJzcnCNdcdDIc/LtdxN8ff/kDzLjxfthQVW2v87dLT4NtJ4+HcZuNhIVLVsDeR57n2M+0qRPgtGMPgckTxkJxUQEsWb4a7nvyFXj17U864zAZjKx5VkaPHAo3X3mmqGVcXFQI6yqq4NV3PoE7HnzOTufBYHR3dNbzomLU8MHw3r/vgmgsBuN3ObrDj5HByBZ0ikI5bcoEeOL5t+DAEy6Bo864CgIBPzx3/3WQn5drr4O5wfbedTs4/ZJb4LCTZ8DA8r7w6B0zEtr692vvw+vvfua6n6mTxotarKdefBNM/79z4N+v/Q/u+dsFIqqMwcgGdNazEo5E4KU3P4Sj/3w17PL7M+Cavz8Mxx62D1z852M69PgYjGx8XgjY/n03XwJf//BLhxwPg5HN6JKgnL59SmDuR8/AoX+6DL7+/mehJv700b/grBm3wVv/+1Kss9moYfDpf+6HA4+/GL7/aZ5j+4vOOBr23WOHpG+RhKfuvRo2VFbDhdfe02HHw2D0hGcFVZzJW44R+2IwshEd/bxccd4fYWB5P/j8m9nw10tOYYWSwehqH8qSokLxWV1TJz63Gr8Z5ASDjrxUC5euhJWr18OUSZu3eV/VNfVt7DGD0TXorGcFzXh77LgNzPxubjv0msHoec/LTttuBQfuvTNcftP97dxrBqNnoNPzUBqGAX+95FT45odfYN6i5eK3Af37QEsoLOp4qqioqoYB/cpava+D9tlZ5Ly69Pp/trnfDEZPfFZef/LW/2/vXkKiiqM4jh9noqzBysIWEoUVFWi1qMxKlJLMhKxBqZ2PFNKSmggtLa0MXWShWUiQC7MsCC2zBz0QF4Eri6yFofYgRfNFkY/AiSnmj6ljLYo7Xpzx+9lc5s7if+/iXH7D/Z8zErByqXjOmC7XKx5LfnG5064fcJd68Z7jJYU5Fkk9cUH6B747/doBd6B7oMzLSJaVyxbJ7vhjE7rOpnWrpODMYUnLuSRNww8XwJXoUSvJ6efEZJop/sv95OSRBEmJM0tx6Z0JWw9wxXrJz05VTWv21+gAJkGgzD2+X7aFrBfzvgzp6OodOd/V80V13832Mjn8kvSZN1e6ekc78f5V0NoAuVaUJafOl0jFg1qnXT/gbrXS3tmjjs3vW8VgMEh+VqpcKasSm83mpDsBXL9eNgeulvDQDZIca1afPTxEjEajfKqvkvSzl1UDKDDVTdOz4CO2bpSYpAxpbe90+O51Y4sMWa0SHLhGHtXUjYw1Wei7QF40vP2vdeyjg8qKsiX3YqmUVz5x6j0A7lQr4xkMHqqL1X4kT8JV6FEvO2PTxGgYbTnYviVIDsZHS1RcmnweE2CBqUyXQJmXmSLmHSGSYMlV+098hveu9PUPqtlh9uOtu8/k9NFEtZm6b2BQPSTqGxoduvDsjQOmWZ7iM99b7fnyX+Gnzje9a1VjUOyvue1d3SU3q1VH3+91rNYf8vUbjTmY/PSqFXNkqJo32dj8UYaGrGqvccahOKl++pw5lHAZetVLy4c2h3Xt9WL7aRvZqwlAp7FB7a/u//W8JbtQblfXOAyf3RURMjx89qUaPts95rVERUmeCo3jBUYmqq69ghyL7I0K++P7uvo3EpOU6dR7Aly5VqLCg+VAfLQsWeyrmhnaOrql8mGtXL1xTzUxAK5Ar3oZb09UGGODgMkwhxIAAADug//yBgAAgCYESgAAAGhCoAQAAIAmBEoAAABoQqAEAACAJgRKAAAAaEKgBAAAgCYESgAAAGhCoAQAAIAmBEoAAABoQqAEAACAJgRKAAAAiBa/AJzDOd6DMY0YAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 700x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Time series plot\n",
    "# ==============================================================================\n",
    "set_dark_theme()\n",
    "fig, ax = plt.subplots(figsize=(7, 3))\n",
    "data_train['production'].plot(ax=ax, label='train', linewidth=1)\n",
    "data_test['production'].plot(ax=ax, label='test', linewidth=1)\n",
    "ax.axvspan(\n",
    "    pd.to_datetime('2012-06'),\n",
    "    pd.to_datetime('2012-10'), \n",
    "    label=\"Shutdown\",\n",
    "    color=\"gray\",\n",
    "    alpha=0.3\n",
    ")\n",
    "ax.set_title('Energy production')\n",
    "ax.set_xlabel(\"\")\n",
    "ax.legend();"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exclude part of the time series\n",
    "\n",
    "Between 2012-06-01 and 2012-09-30, the factory underwent a shutdown. To reduce the impact of these dates on the model, a custom function is created. This function assigns a value of 0 to any index date that falls within the shutdown period or up to 21 days later (lags used by the model), and a value of 1 to all other dates. Observations assigned a weight of 0 have no influence on the model training."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Custom function to create weights\n",
    "# ==============================================================================\n",
    "def custom_weights(index):\n",
    "    \"\"\"\n",
    "    Return 0 if index is between 2012-06-01 and 2012-10-21.\n",
    "    \"\"\"\n",
    "    weights = np.where(\n",
    "                  (index >= '2012-06-01') & (index <= '2012-10-21'),\n",
    "                   0,\n",
    "                   1\n",
    "              )\n",
    "\n",
    "    return weights"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A `ForecasterRecursive` is trained including the `custom_weights` function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a recursive multi-step forecaster (ForecasterRecursive)\n",
    "# ==============================================================================\n",
    "forecaster = ForecasterRecursive(\n",
    "                 estimator   = Ridge(random_state=123),\n",
    "                 lags        = 21,\n",
    "                 weight_func = custom_weights\n",
    "             )"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"admonition note\" name=\"html-admonition\" style=\"background: rgba(255,145,0,.1); padding-top: 0px; padding-bottom: 6px; border-radius: 8px; border-left: 8px solid #ff9100; border-color: #ff9100; padding-left: 10px; padding-right: 10px\">\n",
    "\n",
    "<p class=\"title\">\n",
    "    <i style=\"font-size: 18px; color:#ff9100; border-color: #ff1744;\"></i>\n",
    "    <b style=\"color: #ff9100;\"> <span style=\"color: #ff9100;\">&#9888;</span> Warning</b>\n",
    "</p>\n",
    "\n",
    "If the estimator used in the model's fitting method does not support <code>sample_weight</code> within its <code>fit</code> method, the <code>weight_func</code> argument will be ignored.\n",
    "\n",
    "</div>"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `source_code_weight_func` argument stores the source code of the `weight_func` added to the forecaster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "def custom_weights(index):\n",
      "    \"\"\"\n",
      "    Return 0 if index is between 2012-06-01 and 2012-10-21.\n",
      "    \"\"\"\n",
      "    weights = np.where(\n",
      "                  (index >= '2012-06-01') & (index <= '2012-10-21'),\n",
      "                   0,\n",
      "                   1\n",
      "              )\n",
      "\n",
      "    return weights\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(forecaster.source_code_weight_func)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After creating the forecaster, a [backtesting process](../user_guides/backtesting.html) is performed to simulate its behavior if the test set had been predicted in batches of 12 days."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bbc42dcc557e4f92a5d0517c84da8054",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/31 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean_absolute_error</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>26.821189</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean_absolute_error\n",
       "0            26.821189"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Backtesting: predict batches of 12 days\n",
    "# ==============================================================================\n",
    "cv = TimeSeriesFold(\n",
    "         steps              = 12,\n",
    "         initial_train_size = len(data.loc[:end_train]),\n",
    "         refit              = False\n",
    "     )\n",
    "\n",
    "metric, predictions_backtest = backtesting_forecaster(\n",
    "                                   forecaster = forecaster,\n",
    "                                   y          = data['production'],\n",
    "                                   cv         = cv,\n",
    "                                   metric     = 'mean_absolute_error'\n",
    "                               )\n",
    "\n",
    "metric"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fold</th>\n",
       "      <th>pred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-01-01</th>\n",
       "      <td>0</td>\n",
       "      <td>406.122211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-02</th>\n",
       "      <td>0</td>\n",
       "      <td>444.103631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-03</th>\n",
       "      <td>0</td>\n",
       "      <td>469.424876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-04</th>\n",
       "      <td>0</td>\n",
       "      <td>449.407001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-05</th>\n",
       "      <td>0</td>\n",
       "      <td>414.945674</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            fold        pred\n",
       "2014-01-01     0  406.122211\n",
       "2014-01-02     0  444.103631\n",
       "2014-01-03     0  469.424876\n",
       "2014-01-04     0  449.407001\n",
       "2014-01-05     0  414.945674"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Backtest predictions\n",
    "# ==============================================================================\n",
    "predictions_backtest.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAApQAAAFBCAYAAADJ1D89AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjMsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvZiW1igAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzsXQeYJFXVPdU5TM6zsznvsnlZcs4ggoKKBHMgqSiYQAmiICKYUEQEf0SMJBFFyTkvLBtgc56cZ3p6Olf9332vXk11dXVPz87Mzu7OO98338x0V1e/rq56dd65956roGq5BgkJCQkJCQkJCYk9hGNPXyghISEhISEhISFBkIRSQkJCQkJCQkJiWJCEUkJCQkJCQkJCYliQhFJCQkJCQkJCQmJYkIRSQkJCQkJCQkJiWJCEUkJCQkJCQkJCYliQhFJCQkJCQkJCQmJYkIRSQkJCQkJCQkJiWJCEUkJCQkJCQkJCYliQhFJCQkLiAMDhBy9A43uP46pLzse+gokTqtiYfn7j18d6KBISEqMM12i/gYSExL4JutEPhnO/eDVeX7lur4xHYv89j15buRYf++I1Yz0UCQmJMYQklBIS4xy33/WXrM/tbmzdq2OROLDQ3NqBYz5yKXr7wmM9FAkJiVGGJJQSEuMct9/117EegsQBimQyhS076sd6GBISEnsBModSQkIiL1BuHoU3KVfvQycdgf88cDu2vv4Q3n/xL/jtLd9CTVWZ7etKigpw9Vc/jRcfuRNb33gIG17+G/7+ux/h2MOXZmz7ibNOZO9Bv487Yhkeuudmtr05PF9YEMAPvvVFrHzy/7DtzYfx0qO/xZcvOhuT66oz8vXu/PE32WOHLV9gO7YzTjyCPX/Tdy8e9PObx3bi0QfjX3+8FVtefxAfvPRX3P3T72La5NqM19BY6DU0ts9/8kw8849fsWNAn0uAXvfLH34D7zx1H3a8/Qjefeo+9r/d/ggVZSW4/fqvYvWz97N9Pf33X+LjHz4h67jffOIe9jPYd2rFzKkT8bMbvsZeu/2tR7DmuT/h0T/cgk9//PS040E44uCF7G/xI/I4c+VQVlWU4uarL2H7p8+99rkHcM/tV2PhvBk5jz29Fx2/Ta/+HRtf+Tvuv+M6zJw2Mevnl5CQ2DuQCqWEhMSQ8JlPfAinHHsInnrxLbzxzjosXTAbZ592DObPnoaTz/sa4omksW1dbSUevufHjFDRts+/9i4Cfi9OOnoF/vybG/DtH/0Gf3nkqYz3+NBJR+L4I5bh+VffwZ8e+i8m1laxx70eNx68+yYsmj8Ta9dvxaNPvIDCgiC+9sVP4NBlB2Xs548P/hcfOf1YXHTuqez9rfjUx05jv+9/8L95f/4zTjgcxx+5HP99/g2WO3jQnOk48+QjccSKhTj7M9/G1p0NGa/54be/jEOWzcezL6/Ec6+8g5SqsscXHzQLf7/rhygI+tnx3LRtFyNy537oOJx63KE475Jrsfr9zcZ+ykqKGJGdOqkWb777Pt5a9QGqKstwy/cuw0uvr8JIgQjz3bd+Fx6Pi31n//zvSygqDOKgOdNw2WfPZcfr/Y3bWLrEVZdcgN2NLfjHv541Xk/HJRcmTajGP+/7CWqryvHym6vZ/ifUVODMk4/CiUevwJeu+jGeefntjNfReUPHhZ8X/8Os6ZPYY0sOmoXjzrkcnd29I3YMJCQkhgZJKCUkxjmyVQXHYgn8+v8eyniciN4ZF16JDVt2Go/95sffxEdPPxanHn8YHn/qFeNxUtom1lbi0u/ciseefNl4nMjJw/fczIjWUy+8hfbO7rT3OPGo5bjoKz/AC6+9m/b4pZ85h5HJf/73RVx29W3G47+65x948q+/yBgrkS4aJymRpcV3o6snZDxHJPfoQxfj7fc+wMatu5AvTjnuUHz6qzemEZ4vXPBh9lluvuZSnHfx9zNes2DeDJxy3tcZ8TLjVz/8BjsWl19zGx594kXj8bNOOQp33fod3PGjK3HsOZdB0zT2+He/+ilGJu9+4DHccNuA6vh/f/s3Hv/jTzESINL6m5u/CafLgY9/+fsZRJxIIOH9jdvZDyeUrUNKnfjJ9y9j+7nl139i353AH//xBB659xb84odfxyGnfwH9kWja6047/jBccNl1eOWtNcZjpH5/9Qsfxyc/chLuvO+RYXxyCQmJ4UCGvCUkxjmIENj9XP75c223v/evj6eRScKfH36S/V560Gzjsfmzp7Lw5H+efS2NTBJ6Q2Hc9tu/wO/zsvC5FU++8GYGmSRQaDeVSuHmO+5Pe7yxpR2//8u/bMd7/4NPwOf1sHCpGReecyocDgdTuoYCUtSs6tn//e0/2L6rkRFUUmWtuPO+hzPI5Iol85jCtnL1+jQySfjXU68wMkyh3EOWzmePuVxOnHPGcQj19WcUUq35YAse+W/6PvYUdIyJ5JIKaafqNrV2DGv/RCQpnaG+sZUdFzNWrt6Af/7vJUZqzzjx8IzXPvbkS2lkkvCAfu4tMZ17EhISex9SoZSQGOeYsOTDQ9qeyIsVROgIxUVB47Hli+ay30UFQVsVtLy0mP2eZZP/tmrdpozHKCw8bfIENDS1MTJiBYV/7fDg48/jmq99hoW9f/enfxrkjAgmKZZmRTUf2JEsVVXx1nvr2fgWzp3BxmjGezafh7YjWAmSwKtvr2Fh/AVzp3NyOXUiAn4fe38ilVa8vnItzrOQ5j3BskVz2G8KzY8G6PMQ3lz1PivaseLVt1fjY2cejwVzZ+Chfz+f9txq23OPH+viooJRGa+EhER+kIRSQkJiSOgJ9WU8lkxxYuBwOo3HSkuK2G8qvrErwBEIBvwZj7V1dGU8VhgM8Ocs4XGB9g77x8P9ETz8nxfwmU+cwRRTyu875dhDUV1ZxkLHsXgCQ0Fblvdpa+8yioasaG3PfI3YrrW903Z/LW388eLCoEHMc33+Vv39hwvxfmT5MxqgnNdc421p60obh1XZtiKV4vmoTqcMuElIjCUkoZSQkBgVhPSb/7U/uZuFyYcCPWUwfX9hrspVlpXYvqai3P5xAoVviVBSEQ4RSlGM88DDQwt3s/fP8j6VFaV8nDbqoYbMDyS2qyznr7OCCC+hV99OeDlm+/xUNW0HVdXgdttP9RTatqJH/95qqsozUhtGAiHxObJ+bv649K6UkNi/IJd0EhISo4J31m5kv6m6eSTQF45gx+4mZk9EdjRWiFxDO6zfvIOFxE874XBWlU65jtQBaMv2oXsk2lkQUS7mIUvmsb/Xbtia137WbdjGfpNqagfxOFWzE8jPkYpUqKrcTgU9PMt+enr7GAmlML8Vi+fPynjs3TX8ezvhqOV5fQ7KaXU68r+ViM9N35edqnjEwYvSPreEhMT+AUkoJSQkRgWUa0n5fmSz88mzT7LdZu7MKUYuZT546N/Pwel04pqvfjrt8QnVFfjSBWflfO0fH3yC2Q79/var9WKc/K2CzCAySlY1Znzukx9i+ZOvvLU6I38yG9567wNGaClP0lqYRP8Tcd26o97IDaV8w0eYTVKAFU2ZQZXv55x+rO37UD4qKZTnWb4DyiG1I+EPPv4cCy2T36SdFZOo8hagPFSy/MkXVNTz4uurWJX9ly48O+05IvvkFkD7/O9zb+S9TwkJibGHDHlLSIxzZLMNIvzv+TeYNcye4vKrb8M/fn8TfvaDK5i1zrtrN6E31Ifa6grMmzWV/Zz5qW+io6snr/2RLQxZx5C35IypExkxIYL14VOOYoUrp59wODTd49GKfz/1Kn7wzS8y8tnR2YMnnn1tjz7TUy+8iXt/dg3zodyxu5EphicedTDzQLzm5ruGtK8rrv05/nbXD3HXT77NKttJhZwxZSJOO/5QFhL/2vd/blgGEW6540846pDFzMh98fyZhg8l2Qw998pKZttkxR/+9m9GJm+55lIcfchiNDa3Mz/J5Yvn4ukX38LJxx6Stj19DrIxIrP2h35/E5579V2s37yd5bDS9zWhphKHfeiLxvavvLmafR9//OW1TJ1NJJJ449332feRDd/50W/w2H234rorP8/ya1d/sBkTqiuZn6eqqbjy+l+y3FcJCYn9B5JQSkiMc1jVLjPIX3A4hJLUqNPO/wY+f/6Z+NCJR+CcM45l6iAVtpCJN5EdCkfni2gsjo996Xv41qUXMhXvSxedjd0NLbjj3gdZ1TARSpFraUUimcQjT7zIyNg/Hn82zYB9KHjiudeZVQ2ZqZ909MFsv/955jX8+Fd/xLZdjUPaF6mH5Ol5xZfOY8rnycccwggdWef84u6/Z5ik03Nnf/bbzHuRtiVlctvOBlx982+ZLZEdody8bTc+efG1zMOSXkMFVHSsPvzpbzFrHiuhJJAB++kXXonLP3sujjp0MY49fAkLnW/Z3oA7/vBg2rbX3vp7liF61CGLWJicFGSyNcpFKHc1tOD0C7+BK754HiPj1Kmnry/CrKJ+ec8/0szcJSQk9g8oqFpuk/4uISEhsX/hgnNOwW3XfRXf/uFvshbbUMu+w5YdhKM/cgm272oa0v4pRPyLG7+Or1/3i7SuMBISEhISModSQkJiP4OofjajrqYS3/jSJ1m49emX3rJ93ZIFs1ihywuvrRoymZSQkJCQyA0Z8paQkNiv8Pvbrobb5cSa9VtZPib1hT7pmBXM9PvmX/7R8G8UoOISssChPEKqSL7trj+P2dglJCQkDlRIQikhIbFf4eH/PI9zP3Q8y8mkgpxwJIp3125k7Q//+9zrGdtf/rlzUVtVgZ0NzazI5b11Mj9PQkJCYqQhcyglJCQkJCQkJCSGBZlDKSEhISEhISEhMSxIQikhISEhISEhITEsSEIpISEhISEhISFx4BPKEr8fTkXJ+jw9N9g2e7LtaGxvfV6Ofey2LwsEUJrHa/bFsVu3z7aP/WHs2baj74a+o7Eey3D27XY48v68+9rY7bYfyrm3r419b2+/N8eSz2v31bHn8/z+NHYr9vex0xx8QBHKUrqpOLIPlZ4bbJs92XY0trc+L8c+dtsX+/0oyeM1++LYrdtn28f+MPZs29F3Q9/RWI9lOPv2uFx5f959bex22w/l3NvXxr63t9+bY8nntfvq2PN5fn8auxX7+9hpDj6gCKWEhISEhISEhMS+C0koJSQkJCQkJCQkhgVJKCUkJCQkJCQkJIYFSSglJCQkJCQkJCSGBUkoJSQkJCQkJCQkhgXZy1tCQkJCQkKCYUpdNc494xj43G5EEwnk05uZTGi8bhdiieSIbG99fij7H+mx7M3tlTEYi6Io2N3Yigf//QKGC0koJSQkJCQkJBiZPO/sE3Dn/z2KeDyBRCqVN1FxO50jtr31+aHsf6THsje3V8ZoLOecfjQOXToPb65aj+FAhrwlJCQkJCQk8NHTj8Zv/u9RhCPRsR6KxF7EY0+9iiMPXjDs/UhCacb0RcCiY8Z6FBISEhISEnsdDkWRZHIcIpVSR2Q/klCasfhYYOnxYz0KCQkJCQmJvY58wqYSBya0EdiHJJRmFJUBTvdYj0JCQkJCQkJCYr+CJJRmFJYCLlmnJCEhISEhISExFEhCKeBwAgUlUqGUkJCQkJDYj/DQPTfjB9/64ojt7+c3fh1/+Pn3Rmx/4wWSUAoQmVQcgEsSSgkJCQkJCQmJoUDGd83hboJTHhIJCQkJCYn9AaQmHnHwQvbzpQvPZo8ddeaX4fG68f1vfB6HLpuP/kgUL77+Hm647R50dveybT500hG48uLzMXVSLaLRGNZt2IbPfv1HuOyz5+C8s05k2zS+9zj7fe4Xr8brK9eN4afcPyDZk0BhGf8tQ94SEhISEhL7Ba679W7MmDIBG7bsxE/v/DMz76aS5WfuvxV/efQpRiJ9Xg++9/XP4q5bv41PfPn7qKooxZ0//hZ+9Mv78L/nXkdJYQGWL57Lusb89o+PYta0SSgIBvCN63/B3qO7p2+sP+Z+AUkorYRSFuVISEhISEgMIFjM08JyWM6oTie0VCqv3Q22vdbXDUTzI3Ghvn7EE0lEojG0dXQzQvmNL3+SKY633PEnY7srr/8l3nnqPkyfPAHBgB9utwtPPPsaGpva0OLswLqN2wzrnEgsDo/HzfYnkT8ke5q5BGjYwi2DRHEO5VJqI2P0KSEhISEhsV9j6QnA0R/NuUlyiLvMuf3LjwKv/wt7inmzp+KIFQux+bV/ZDw3ZVItXnx9FV5+4z089+Cv8eLr7+KVN1fjX0++jO5QeI/fU0ISSuAjXwHe/t+AQilUykR8LEclISEhISGxb2DVc8Dmd3Nu4nI6kcxToRx0e1Ioh4Gg34enX3wbN/3yvoznWto6oaoqzrvkWqxYMg/HHr4UnznvQ/jmZRfiQxd9E7sbW4b13uMZklC6PcC0hYCaAqL9gC/A8ygloZSQkJCQkADCPfwnCyjM7HA6oaRSeXVcGWx7lgfpdOY9vEQiCadjwLSGwt2nnXA4I4e52gq+/d56rHxvPX59z4N49d934/QTDsPdDzyGRCKRtj+J/DC+jxiFtgm104DyCUB3K/9fVnpLSEhISEjsFyDiuHThHEycUIXSkiLc/48nUFJcgDtv+RYWHzQLUybWMCXy5z+4Ag6HA0sXzMZXv/BxLJo/ExNqKnHaCYehrLQYm7fX6/trxbxZUzFjSh3KSorgcuVPbsczxjehNK+ASJns0qVu6UUpISEhISGxX+CuPz7KlMgXH74T6174MzxuNz7y2W8zlfGvv72R5Ure+K0voScUZuHuULgfhy07CA/8+nq8/NhduOrSC3Hj7ffi+VffYfv78yNPYuvOBvz3Lz9j+6PQuMTgGN9SHBXgmNElFEpJKCUkJCQkJPYHbNvViLM+8y0jXO52OpFIpfDFq35su/2W7fW48PIbMrYX6OzqxfmXXreXRj9OCeWbT9yDSROqMx6/7+//wTU/vgtejxvXX/UFnHXq0ezvF15bhatv/i3aOwcSbOtqKvHj712KIw9ehHAkggcffw43/+qPOfMcRg0itN3RBJTXDoS8pXWQhISEhISEhETeGBJzOv3CK9MSVefOnIK//+5HePzpV9j/N3zzizjp6BW4+Fs/QW9fGDd99xLc+7OrcfZnv8Oep9yF+++4Dm0dXTjrs99CVUUZfvXDbyCRTKb5Re11hfL914C5K4D2Bv6/VCglJCQkJCQkJEYnh5JkYDL6FD8nHbMC23c1spZEhQUBnP/Rk3HD7ffg1bfXYO36rcxIdMWS+Vi2cA57PSXFzp4+CV+55md4f+N2lq9w650P4LOf+BDcY6EKCkLZtA249/tARDdSlUU5EhISEhISEhJ5Y4+ZExHAc884Hr974J/s/0XzZrJE2JffXG1ss2VHPeobW1lLo3fXbsTBi+ay9kjmEDiFxX/y/csxZ8Zk5lSf9f1yWAiI53JtY7et5vYgQQdB05iFgaap/H+Pl/0/1H3ns731+T0d+0iMZTyNPdv2+bxmXx273Wew7mN/GHuu7faFsQxn3y49ojOW59hI7nso596+Nva9vf1YzgN7un9F/CjMuIf/1gY3Ahrp7a3PD2X/Yz12K/aXsdMzniz3j1EnlFRmX1QYxD/+9Sz7n3pjxuIJ9Fqc5ts6u1FVzls2VVaUZLQyEuSysqIU2Jj9/aoKCwcdUz7bmLeNF5eAgtwVAT/8JSVI+oPYDaC8uASBkpI93nc+21ufH+rYR3Is42nsw3nNvjZ2u+2z7WN/GPuBOJayYHBIr9uXxp5r+6GcewfaOTDU7ffmWIZ7n/S6XWkkQiyI8sVIb299fij7H+uxW7Gvj52++zoL7xkq9phQnv+Rk1nImlzn9wZaQ6G0Kiwz6AKgiyTXNnbbxlx8sm/v7YGjuxtalPRJoCMaQ1d395D3nc/21uf3dOwjMZbxNPZs2xMGe82+Onbz9tn2sT+MPdd2hLEey3D23RkOM1I5lufYSO57KOfevjb2vb393hwLYbDX5rP/WCLJniMFi0hHUlWh5al8jeT21ueHsv+xHrsV+8vY6btv0HmP3Tw8aoSyrrYSRx+6OK0kv7W9i1V2k2ppVikry0rQqquSbe3dzFDUjIoyzojb2rtyvied5PFBLrJ8tjFvm+R+/EgmEgC9Lhbl/ytO/v8e7juf7a3PD3XsIzmW8TT24bxmXxu73fbZ9rE/jP1AHAtN3EN53b409lzbD+XcO9DOgaFuvzfGMpTX5tqGKAajGTrZINKRT+ebEd/e+vxQ9j/WY7diPxk7/T/Ue+eIGJt/8uyT0N7Zg2deftt4bM36LYgnEjjqkMXGY+QyT87176zewP5fuWYDqwwvLy02tjnm8CWMgG7atgtjVpSj6m3qU1yhlEU5EhISEhISEhL5Y8jMiSTT8846iflHmr0jQ339+OujT+OGq76A7p4Qc6K/6bsXY+Xq9awgh/Di66uwadtu3HHTlfjRL/4PleWl+M7lF+G+f/wH8YRO6saCUApWTuydenrLTjkSEhISEhISEqOnUB5z2BKmOv7tn09nPHfDbfcw1fL3t1+NR/9wCwuDf+HKm43nqeXRp792I1Kqisf/eBt+fdNVeOjx5/HTO/+MMYFIPiYSKZBMSkIpISEhISEhkYE3nrgHnz//w8b/je89jtOOP2xY+xyJfeyXCiWpjBOWDBxMM6jKmzrm0E82NDS14VNf+QH2CThsCCWFvWXIW0JCQkJCQmIQLD7xU+jp1T2sB8FVl5zPiOPJ512xx/vYlzG+mZNQKM2JqElJKCUkJCQkJA5UkI82degbCVitEIezD14mvP9ifDMnquY2F+UQUjLkLSEhISEhsb/goXtuxsYtO9nf537oeCRTKdz/jydwq55O9+YT97Aaj2mTJzCF8InnXsc3rvsFDlkyH1d/7dNYPH8mOrt78d/n3sDNv/ojItEYex0VEP/shq/hqEMXM9L3k9/8yTZc/flv3IT/Pf8G+7+2qhzXfuNzOPaIZcz5ZvO23bj+1rsxbUodrrrkAuM1hK9f9wvm5S328aS+Dype/sG3v4Tli+aysTzx7Gu44bZ70R/hTjQ/v/HrKC4M4q1VH+CST3+EEeTHnnwZ1/3090gmuUD2mU+cgS9ddDYmVFcg1BfGm+9+gIu/dcuofg/jm1A6s4W8JaGUkJCQkJDYX/DxD5+Av/7zaZx50VVYunA2fvy9y1Df3Ia/PPIUe/6ST38UP7/7b/jZ7/7K/p8ysQZ/vvMG3PqbB/CdG3+N4uIC/Oi7l+Dmqy/BN67/JdvmFz/8Omoqy/DxL32PKZo/+s6XUVGa3fw74Pfh4Xt/jObWDnzuih+htaMLi+bNgENx4F9Pvow5M6bguCOX4byLv28UM1vh93nx5zt/gHfWbMQZF17JrBVvu/6ruInGdd0vjO2OOHghWts6cf7F12LihGr89tZvs26D9HkXzZ+JH377y/ja93+Gt1evR2lRIQ5ddhBGG+ObUFqrvEXIeyz6iktISEhISOyDqHFrqPVkf55CtS6HiqSanx/iYNs3x4GOAROZvNDY3I7rf3oP2/eu+mbMmj4ZX77wbINQvvr2GvzuT7xVNOG2676KR554Eff8+V/MwDuxI4Vrf3I3Hr73Znz3pjtRV1OJE486GKdfeCVWv7+ZveaqG+7AS//8bdYxfPSMY5mqSUSwW8+J3Lm7ie8/lUI4EkEqlcoZJj/79GPg9XoYGSR1cuPWXfjeLXfhj7+8Fjf94j6ju2BPqA/fu+V3cCoKNmzdhWdeXomjD1nMPi+NndTMp196G+H+CKtdIbI52iH18c2cbBXKpFQoJSQkJCQkdHy5WsN1kwajikNkgDm2v3G3gluahrY3YU8o8M6aDbj4Ux+BQ28zuPqDLWnPz58zDfNmTcU5ZxybZovodDoxqa6a+WgnEkmsMb1uy456gyja4aA507Fuw7ac2wyGmVMnYv2m7UbYnfD2e+vZuGZMrTMIJRFNcs6hxwmt7Z0sVE546Y33UN/Uijf+/Xs8/9q7eP61d/C/595A1LTP0cD4JpQO/ePLohwJCQkJCQlb3N2i4PEuZRDFUW/pl8f+BtueFMqRhsg/FAj6fXjgof/hD399PGMspOgRoRwqoqNM2MwQuZIC1P1GkGdSJU89/+ssLH7s4UvxrUsvZPmbH7rwSkT604/DSGJ8MycKebPWaKZTWhblSEhISEhIGGhOKGjWG8llI4hupwOJVP4h71zb8+eHNsalC+ek/b9s4Rxs39XIVDw7rN2wFbOnT8IOU0jaPJYt2+vhdrtYPqIIeRPJLCkqyDqG9Zt34IKPnsK2sVMpqYGLIH3ZQCrouR8+geVSCpVyxZJ5LFS+dUcD8gU1nnn5zdXs5/a7/ooNL/8NR65YhGdefAujhT1qvXjAgKRic7ibIEPeEhISEhIS+xXqaipw/VVfYKTvrFOPxufPPxP3/IVXU9vhN//3MA5ePA8/+u7FmD97GqZNrsWpxx3KOvwRtu5swHOvvINbv385li6YjYXzZrDimEgkuwr5z/++hLaOLvzh599jJHByXTXOOPEIRm4J9Y2t7LGD5kxDWUkRPO5MTe+f/30RsVgcv/zhNzBnxmSmMv7oOxfjof+8YIS7B8NJR6/AF87/MHufutpKVrDkcCjsM40mpEJpJZTJOODxjdWIJCQkJCQkJIaIh/79PHxeD/79wO1Mlbz3L4/jgYf/l1NNPOeLV+O7X/kU/nHPzVAUYMfuZvzrqZeNbb5x/S9w2/VfY5Xb7cw26AF8+/KKrPtMJJP45KXX4forv4A/3XE9XC4nazd9/U/uZs//55lXcfoJh+PB39/MVExhG2RGNBrHhZddz2yDnvjzz9Jsg/JFbyiM0088HFdecj58Hg+27WrEZVffhk1bdzE1drQgCaU5f9JQKMf3YZGQkJCQkNifQGSOqryvufm3Rghb4NAzvmj7GgplX3DpdbYhbwJVY3/mazemPfbIf55PI2XWzoENTW34ssnvkYfvnUbI2/ycdR8iS3XDlp34xJe5tZAdhH2QOauVPrvAW+99gI998ZqM1412lbcMeWcolJRDmcMfQUJCQkJCQkJCIg3jm1BSlbe5Sw5B9vKWkJCQkJCQkBgSxjdzsgt5S9sgCQkJCQmJ/QZ24V2JvY/xrVBmq/KWtkESEhISEhISEnljfBNKuypvGfKWkJCQkBiHGO2iDYkD+7sf34TSaRfylgqlhISEhMT4g6pprIOMxPiC0zkyVHB8E0pbH0pSKCWhlJCQkJAYX3j0vy/j8s99VJLKcYazTzkSr65cN+z9jO/YLqvyliFvCQkJCQmJnQ0t+Ptjz+FLF54Jv8eDaCKRdytFr9uFWCI5Ittbnx/K/kd6LHtze2UMxqIoCnY3tuLNVesxXIxv5sRC3lbbIBnylpCQkJAYv6TyN//3KOpKStDQ3Y24NS3MBh6nc0S3tz4/lP2P9Fj25vaefWgse4JxHvJ22CuUBBn2lpCQkJCQkJDIC+OcUGbJoSS4xrd4KyEhISEhISGRL8Y5oXTZV3kTZB6lhISEhISEhEReGN+EMpuxOXtOhrwlJCQkJCQkJPLB+CaU2YzNCTLkLSEhISEhISGRFyShzJZDKRVKCQkJCQkJCYm8ML4JpV2nHBHyltZBEhISEhISEhJ5YXwTypwKpQx5S0hISEhISEjkg3FOKO065ciiHAkJCQkJCQmJoWB8E0q7TjmGD6UklBISEhISEhIS+WB8E8pcVd4jEfImlbOgZPj7kZCQkJCQkJDYhyEJ5WgW5Sw7Abjoe8Pfj4SEhISEhITEPozxTSido1yU4y8EfMHh70dCQkJCQkJCYh/G+CaUdiFv8f9IFOWQyknvISEhISEhISFxAGN8E0pSIa0hb0IiPjIhb+q2QyqohISEhISEhMQBjPFNKJlCaanyFoU5I1WUI/0sJSQkJCQkJA5wSEJpDXkTNA1wjMChIZVTcQCKMvx9SUhISEhISEjsoxjfhNKu9SKBSOZIEEqRhylVSgkJCQkJCYkDGOOWUGq5FEp6jJTF4ULkYcrCHAkJCQkJCYkDGOOWUBokz5ZQaiNDAqkohyAVSgkJCQkJCYkDGJJQqnsh5C0VSgkJCQkJCYkDGJJQ2uVQaurIhrylQikhISEhISFxAGP8EkpnLoVSHRlVUSqUEhISEhISEuMA45dQ7o2Qt1QoJSQkJCQkJMYBJKFMZVMoRyKHUieSUqGUkJCQkJCQOIAxfgmlEfJOZsmhdO4VhVILFHELIwkJCQkJCQmJ/RTjl1DmVChH2tg8Czn1BpC45DbEqqcN/70kJCQkJCQkJMYIQ2ZNNVVluOOmK7HuhT9j6xsP4dkH78Ci+TPTtvnWpRdi1dN/ZM///a4fYtrk2rTnS4oK8Oubr8LGV/6O9S//Fbdf/1UE/D7sTWgO1yBFOXvB2NwXYNuk/AXDfy8JCQkJCQkJiTHCkFhTcWEQj913K5LJFC76yg047pzLcePP/oCe3j5jm8s/ey4+f8GZ+O5Nd+LMT30T/ZEo/nLnjfB6dHIF4Nc3fxNzZkzGJy+5Fp/56g9x6PIF+Ol1X8E+U+VNIe9h5j2yMLbbkzvkrT+uCSVTQkJCQkJCQuJAJ5SXf+5jaGxuxzeu/yXeW7cZuxtb8OLrq7CzvtnY5osXnoVf/v4fePKFN7F+8w587dqfo7qyDKcdfxh7fua0iTjhqOW46gd3YNW6TXjrvQ/w/Vt+h7NPPZptd8CEvM2ENBs5NQilrAKXkJCQkJCQ2H8xJCZzyrGH4IXXV+F3P/0ODl++AM2tHbjvH0/gL488xZ6fXFfNSOHLb75nvCbU149Vazdh+eK5eOzJl3Hworno7u3Dmg+2GNvQ9qqqYemC2fjf82/Yvrc7Wx6i6blc21i3dbndoHIcNzQoltclNA2KwwmX0zmkfaeNxetDQn/M5fbAYdkP/VY9XjYGIpRDGfuQxzJC21uf35PjPlZjz7Z9Pq/ZV8du9xms+9gfxp5ru31hLMPZt0tfmI7lOTaS+x7KubevjX1vbz+W88Bw9z/Wx/FAvNe49+OxjwqhnDyxBp/++Om4+4F/4o57HsTiBbPww29/GYlEEg8+/hyqKkrZdm0d3Wmva+vsRlU5f66yohQdnenPp1IquntDxuvtUFVYOOj48tlGoCRYCNJVqwuCcKslac81Ox1QvD5Ul5Ts0b4JFcWl2KX/XVZYhKBpX2J/0eJSNOmEcij7H+pYRnp76/P709iH85p9bex222fbx/4w9gNxLGXB4JBety+NPdf2Qzn3DrRzYKjb782xjPR9cqyP44F0r6naj8c+KoTS4VCYsnjLHX9i/6/buA1zZ0zBpz52OiOUo4nWUAgJu/C0zqLpAOXaxrptVyzG/m/p7oLSm05wE3H+XEN395D2bd5/WzRqPNYRjaK7m7+HeX+xIr4NEUrr/jUKk5dWQ+lo3KPPORrbW5/fk+M+VmPPtj1hsNfsq2M3b59tH/vD2HNtRxjrsQxn353hMCOVY3mOjeS+h3Lu7Wtj39vb782xEAZ77b469vFyr2ndj8c+KoSyta0Lm7buTnts8/bdOOOkI/jz7V3sd2V5ifE3+7+sBO9v2sb+bmvvQnlZulrndDpQUlSY9hor6MPHBzkA+WwjkILCX5OIZ+ZR0v9OV9q+hrJvQtLkY5lSHEhZXkv7SyqKUZSTsf+5hwCnfwH42cUZhUNDHctIb299fij7H+uxD+c1+9rY7bbPto/9YewH4liS5Bixj5xjI7nvoZx7B9o5MNTt98ZYhvLafW3s4+Vek9iPx54vhlR58vbq9ZgxtS7tselT6tDQ1Mr+3tXQgpa2Thx1yGLj+YKgH0sXzsY7qzew/1eu2cBsgxbOm2FsQ9uT+klFOvtOp5xhVnmbC22yFuXw6m7NLk/BF+RV4vRbQkJCQkJCQmIfxpAI5d0PPIZlC+fgq1/4OKZOqsVHTz8WF517Kv7v7/8xtrnnz//CFV86jxXwzJ05Bb/60ZWMZIpimy3b6/HcK+/gtuu+iiULZmHFknn40XcvZgU7tN2+YRs0AlXewoMyrypvG9sgl245JD0qJSQkJCQkJPZxDCnkvfr9zfjClTfj6q99Gt/48iexu6EF1/3093j0iReNbX5z38PMpPzWa7+CosIg3l71AS687HrE4qLmGfjKNbfhpqsvwT9+9yNW3f3Es6/h+z+5G3sTLEcxl7G5MkxCaSaJ2WyBXDlsgwQhJUJJY/nU96E++xcgmj0tQEJCQkJCQkJiLDBkA8RnXn6b/eTCT3/7Z/aTDWQbdPnVt2FMMRihHGbIG0MKebuyE1IilMEioG4mtIo6oF4SSgkJCQkJCYl9C7KX92gZm5tD3oN2yrF5XnTZIUIZKNL3KQ3QJSQkJCQkJPY9jF9CSTmUrAKTNUkc+V7eQmGkKvJs5qDOPEPepFCa9ykhISEhISEhsQ9hfCuUKvWpgX0vb5Ptz55AE4QwHskj5O3OHfIWCqVs0SghISEhISGxD2J8E8psPkwjGfKOR/esKMctCaWEhISEhITE/oFxTChd9gU5IxbydgGpJJBMZFcoaQz5FuVkUzIlJCQkJCQkJMYY4zyHMpU95D3cKm9SKIlQ6l137LfRH5dFORISEhISEhL7McYtQ9EGC3kP24fSxdVJytMcLIdSVyrtnmOEksLmYp8SEhISEhISEvsYXOO7KGf0Qt6sKIcRytTgVd4ul95Z3CYHk1ovJuNp20tISEhISEhI7EsYvwxl0JD3CNgGpRI87D2YD6XDjlB6+PhIoWT2RpJQSkhISEhISOybGL85lCzkncxR5T3cHEoR8s6xL1HlbTZBN55zA309/HdhKX9MFuVISEhISEhI7IMY34QyV8h7JHp5E6HMVZRj5FDaEE4ikqFOfayO7NXgEhISEhISEhJjjPFLKHOFvEfCNsio8s5VlJOrU44HCJn6dscisspbQkJCQkJCYp/E+CWUuaq8R8I2yJlPUU6OTjks5G0ilL0dMuQtISEhISEhsU9iHBPKXMbmw7cNYnmRoijHzhaIIIimwwHN+n4s5G0ilBT+liFvCQkJCQkJiX0Q45dQjnbI2/Ch5AplqUvDzuUpzPFp6aRReEyaC3MUhb++P8QJKY0n1C0JpYSEhISEhMQ+Ccf4NjbPVuWtDp+8pSmUTkz3AnUeYLaZUNJ7UG6k+Nv8WgL5T0b6gEiI/y1D3hISEsPFGV8AVpw61qOQkJA4wDB+Ja+cVd7i8Qx3yD3MoXShSueCxS4NSJq2sVMoqSCHQK8nQqlpjJiSAbqEhITEHqNqErD4WP432ZE997exHpGEhMQBgnGrUOb0oaSiHLaNY5g+lHovb4cTlW6uTBab63OcTihxoVC6syuU/b2cXGbLxZSQkJDIBwuPBsK9wLN/AQ49A5i+cKxHJCEhcYBg/BJKCjHnyqEkDKfS29IpRyiUJaRQmrfJGfJOAOvfBNa/xfcjFUoJCYnhpPkcdATw/mvAW/8DWnYCS08Y62FJSEgcIBi/hDKXbZAgmsNQKNN6eTucAyFvM0clgqgTSi1byPvdZ4H3nufkVOZQSkhI7CG0aQuAYBGw9mX+wLvPATOXAoVlYz00CQmJAwDjl1AO1st7uCHvNIWSQt6wCXm7TSHvLEU5Arl6gktISEgMAnXKQUBnM9C6mz/wwetAIgYsOW6shyYhIXEAYPwSysGqvAnKMELeZoWShbw1m5C3E4jZFOUIJZJeLyAJpYSEhB3mHwYsO3Hg/6Jy++08Pm5FJkAFgZRSM/cQ7G1Eq6chfunPAG9gr7+3hITE6GD8EsqcOZTDD3lzH0pTUY6Xk8HiIJ9ANRHativKcZtC3gK0L5ebv05CQkJCzCPHfGyAUE6eC1x6GxAoytyY5pWEKepB6G4DAgXY20gUV/Aq81lL9vp7S0hIjA7GuQ/lKIa8hQ+lKopyLFXeesGPIopyzAU3TruQt04uh9sSUkJC4oCBVjsdKK0CiKARKur4HFFQnLmt28tD3GbE+sdEJWRjIcxZsdffW0JCYnQwbgllXiHvPSRvGvlXik45RFoVB6qcKXS5Aih2qOkhbt2HMq2ft7nKW0AfqybD3hISEjrUeYcMhLP9BQPE0he0VyiTNoSS5hRRCLiXoIr3m7YQEORSQkJiv8b4JZT5hLz3sJ+3Qfr0opxiLQ6PAmz216JESaaTVbuiHNuQd2LfJpST5nDTZAkJiZHB0R8FjvtE1qc1RYFK+Y/1mwdyJ4srsxNKl03IO9rPf3v92Jsw1FKa62Ys2qvvLSEhMToYv4QyZ6ec4YW8DdKnF+VUJXrZv5sCNShCAgplPukqpGLXKYfUShqDeXz7ukJ5/HncKFlCQmJkQFXZy0/Kqh7GqqYCBaXAG//hD5A6WZJLobQLeUeybz+KUN1eKD3tQPMOYPbBe/W9JSQkRgfjl1A688mhdI4MoYxzQkkKJR3wAoc2oEiysHgysyjHrE6acii1fbVbDikcMnQlITFyCBTyUPbMxbZPJ4lMEna8z5VHIpQ5Qt6aXVFONDw2CiVTS2PArg3AhOl79b0lJCRGB+OXUObMoRypkDdVeSdRaVIoCUVmQplKQCGyaC3KEUU45ipvtu99tCjHQ4Ry7+ZhSUiMGYgEBTMLX0acUBLmH277tOrx8kgGEbPeDqB8wkB1tz9LDmVWhXLvFuaoNJZ4DGjdBZRUysWohMQBgPFLKPNqvTgCIe8UKZQ9SELBDl8Ve7jIqQ4U4SSTUKwKJYW/mZKg5RfyHu0bWz4gJWUvJ/aPFDShBElI5AMiQBdeAxxy+ugueKnIhkzIKcfQRkFU3T6jqA+97dwySERY8gh5T/JovCiHsJcrvXkOZRRoq+cL98q6vfr+EhISI49xnkM5OlXeA+pj0sihbHP40enik3yhWaFUOaHUzAqly40zulZj93IVTkEqBaG0hrypndplt/ObzxiBjdDr229VhuTZlwFHnzPWw5DYX3DiBXzxJPIVcyB+zMfQO//Iob+HuJ7ffYa/F1VD25EyUdTXQwplLf+buuEMUpSzMKBh+3IVh3mifL4bQsibLNeSp33O3utyCFXeCpHb9gb+/pWyoE9CYn/HuCSUzNaH1MdR6uXNPC7FfijkHe9Fq6sQ3YJQuhwGoVSyKJRz+htR6wFqPJYcSqtCWVbLbxTkPzdWoBsbqQz7KaHUCsttffskJKxQp8wHZi/nBC5bRxoTkjOWoPOws6CJfMd8Ichayy4eGiYTcOtYPL6Boj4qcGFvmADaGjJC3hpdn8zKjBPKGbogf2GlysPeQ1Ao42W1UBcdM6zcR06GY3y8Xc1A5cQ93peEhMS+gXFJKA2imE2hFEU5yjAJpVmhdBehB5wMFvg8aSqmHaEsS/SxPycZhFIfq5VQFpTw35Q/NVYQ4eL9NYeS1CDKAZWQGATq9EVAVyuw5sW8CKXmDbAClNSxHxvaGwV1QtnfC0T6bCMQRCiNHEgKebPfHXx7i0LJchYJROIA1OqNFj5ersEVDQ2JUCaKdGXWlCZCi/TKw0+Bwy53M5sPJYW8Ca310nJMQuIAwLgklANFM6nRCXlbFEqq8m71liDZ24U+hxeF1IZR2ASxohxqq2gOeXtQkuS5TXWeQXwohXJRMYaEUoTL9kOFkpF/Gr/MoZTIB3TdUmU0KYK0mDMvBC1glM0XgKdtN9SDjhhaFEEU5FDv7WyEkql8QqHs0H+38fFZCCWrqiboxuYU/YipQIUbOKVj9ZCKcpKiktx0vQcKCrBRfRL/WuhGqUvLU6HUK87bdsuQt4TEAYDxSSjNhG9UQt5CAU2xn2nRVjQEqoCuFnS7AihwOwdIZyplr1AmuZ3HJK8lh3IfVCi1/VihTHn1G69UKCXyAREhChsLAldUlnVTRuKcLhR98ApfpNbNGhqhpPchwpiFUGqsKEfkUOoKZXd7bkKp51BSKs17YWBdP3B+1ztDyqG0UyiL/R74tAROcnbilQUq3ArNWxouqFBR5MwkmKSYKoZCuZt/3n2huFBCQmKPMS4JpUEUs9kGDbOX90DIO4VKxDE51oF3iqYD3a0sj7LQrUDLqVC6UZrqt4S8s/hQ7gOEciDkTYqFgv0JqlBmqKhIQmIw0HVLRI9Cy4QcYW9VX6Q4SWXsbh1aFIFyKMMh/ncOhdLIoQx18fnMUCgDadei0epQr/Ke4NbQlAD+06XgyOiuIRmbJ4oqMxaQAS//+7Ky0zDHD5xdpuG4IuD+WRoLq1vBCK4efmeV3oSTLgJOvghQMucQloMqVUwJiX0a45JQGqRMHf2Q93I3J4bvFE5n4asepw9F9HRaDmXC0svbg9IUVx4mCoUymw8lTbRt9ZjgUzC9IHv4bVRhVvfcYzSGPURK3EhlyFtCgJSyUz+Tma9sGHIngFAnf0CEf22g6qqfI9YPpaNxiISykOdPEqK5ciijA4vgR34FrH6RE0rK/zapjsYC1qRQNsYVNMSB6lQ45/kv8i0zQ94Drwl6+LF6ufZgvNwLXFyt4aoJfB6dZdk1FQgZxuaE7jagvRGYOh84+BRbkp46/Exu1TSGbhYSEhK54Rg3vnGl3APSqiCOirG5qShnuTfG7IK2+ypZeKobbhQ51EGLckrVaLpCSTcMlfwr03MtWTXnzvW4detfcPdMZWxD3mxM+1cepSqKESShlBA49HRg2YlAaXV2hZKuWVIFcymU+rnliEWgEGEqH0oOZREQ0RVKUjgHy6EkbHlPz7nUu9+YCmQGQt6iKAdojgMtcQVeqChx288dX6xSsftgFScXa0buY0pUoJOxuhiuh89fvUU1+F2nH8cXA6eXAhHNgVlByyJYz700Qt6Ubfr77wJ/u1Uftw1pJMWVPs+RZ+c4aBISEmOJ8UEoT7wQOOEC+xzH0Qx5k0LpjeOdwmk8jBOLoEdzoUhJcUJJZJImVpuinDItinCKFErTjknJNIe8Rbh75weY1d+EOqFm7m2Yydh+lkdpKJTC+khifIPO5cXH8b/tKp+JmOnWOyzsnUfI2xGPcIWyuDz/hQsplGFdocyWQ8lsg/QcSrt2iqYwtlHlnYjBpWiodIOFvFv1hlzVjsy58LgiFXdM06BqwCcrdEJZoi/Mac4yK5RkhUaHxOXHI87JbL/18OP+CcdhZqFlThBEVIS8BehzErLli1LkiIg+WaVJSEjscxgfd1CqhDZXIJttfUYz5J1KYbk/wcPdhHgU3aoDRUjqnnB8NrcqlIrTiRItjvf7gRo39AR3vr80hVIQyo4mTIu0otqR5fPs1ZD3/qZQmnLHZB6lxOJjByqefTaFKkTM9OuWEUoiiVmQ0kPOThHyJpD5+LxDB7raZAOpgKQ2CqJF15WpE5Vmp1DmIJTmopxqN+BQSKFU0CIIpWIhdwBunpTC633ATxsVnFWm8XlIj/QoZEhuutaDLgUpKIjAiXjlJHwxOgefX/x1rA/WYYYzCsXc9Uu8LpGNUOoV7lYSuvldfsw/cz1APpgSEhL7FMYHoSTTalPu4eA5lCNjbF7rTKDOrWGlIJSkUKYUFGsxvV83J4CKmq5QFisp9sWs6VfYxE/hKQaWa+nKsAwqjnSiLNXPiKqPuvCMZch7fyOUZrsUWek9bnFCkYZPV2o8h2/jyqwKJctFTOSpUNLrEzEoagpKZxN/sG4mcMYX+PsMmkNpIpRW5Y4IIs0zeSqURg5lMm7MJ40U8tYJZRViGcUwlDv5bLeCv7crKHUBJxSTQlnNQvjss5tC3gVOoNfh5R6dk+biiZOuxHPN/dgcd8MHdSB1xzxfWAkl/U9k3UahvLxvFe5v+xdw3w2cWH7oi2PbzEFCQmI8EkqFJ9mLCdUc8h7Mh3KwEGjN1AG/OCuh1FQsD3Jyx0LehHgEPUkNxWqMt1rUK7epW45ZoSxV+ONr9Da7k8S8zZRMi0IZj2EaBm4qVTatvkcdpOyJMOD+GPIWCwiZRzlu8dkqDT+c5uD51m/9j58Tg4W8Wbccsg1Ssoa8Fd14XCESSsUnR5zFz7Ncpuiij7coyrEjlPq5Kqq8qS/3T6eoWBCg/tx6O0VzyJtym2kMmmZ036KQd08KiGkKquM9lgWVhjIX0JHk89CmCHBOmQattAqu3nYoFK42LR4LnBp6FQ/QXg8cdDgnp0/dj81J/mazzbvW5wjWetGEOo+GOzbeC5eNJ+YRsXpckNyKiWof2y9DrT6vSkhI7BM48AlloIBP0Obcw5EKeX/0q8DykzIf19s6Ur9cmpB3e/WbRyyKaDQGHymSdEPQCS0plIaCQN0UNX7DWhvmN6qJngEvyvSQdynQ14VpJh5UPRZ8jj5LX8/+qVASaaDiCoIklOMWZMZd50yitnUTUL8peztCUZRDIJWOCKbNotKo8hZqIYHCxLS4pfklR6jcII65CKWo4I5F8KlKFeuXqvjGBE4qWUA81p+pUOrjJuUxqQFtbN2qoDnl4oTSROQKHBrcDk4oaZuHOxRm/zOlwAM3deWhghrT9VKgqOijTmD0GQkvPczGvzMGJODATJ855K2/zhKu/0ylhkvbXsZCry6bmlCl26ixXE56HfUrr5qc/RhKSEjsdRz4hDKo5xmmhbwHMTanCZkKcwYLedOEbRMmZftXU6wbxW5ahItQUiyCeLiHGQBrVPEpFEqL8liqE8pdJGokBxRKJWkpyiksAfq6Mc3LE+cJlB+1t6HRMRA3v/1QoVSEKbQklOMWosp5+Yan+QNRImRZFEqyDSJ0tfDfk+dkXawoROwERB4lWftQjmS2a0VUURsh71AGoRRhY3+iH7dO0fDvLuBLWxWcXAIso8gIK+Sx5FDqofoJHh7qpnaJhNaUA1WJnjSboRI9daYzybe5vVFh5PIvHY8j0NXEw9NmhRIp9GpOYP1bwMqngXefY4+nwr3Y6i1Ptw7KUpRzeil/z0UuEwnXUUHWRoJQih7n1dkJ5QMzE7imThcGJCQk9goc4yJ/kmAibIaXY1ZCqauUg4W8KdRrSpQf2D+v4K5xazxHSSie8QiivVzJc1fVGd6S5EOZFvLW+Mq9k9TNOCmUyKJQlhgK5XqV3/yqfGMQ896vFUoilG38H5lDeeCCTLFt2iQmgyVInPt1lBTzhefBrWv4E0QE7brHmBVKUuO2rQGO+4StZyX5RCpETAXWvwm8/STw/mv8/8LywdsusrFEeDTFJuR9ka+Thaav3unAH1sVbI4A3yEiZemWw3tnx0welAO7akkoqCGF0qTIljj5nNVB85fDie6UgvN3BLA4Uo8ret/k+zLnUCKJkOrgx+TpPw04ZfR1Y0tgAmb5tfS2iwRTyLvcpeFQ/eMtgr44FdvT15fsw0q1EEuCwHzaV8tOoGqK/fEDcEyhhhsmaThRtzuSkJAYfRz4hFK08zLfTAYLeUMngblC3sJmxhSqHti/g5FVqtCmSkpQiJsm2HgMsRifyb0+X7pCKYpyHE6UJvtZSCqU4hM/5RaJ8aYZm1PIO8QVys0JF9pdBagKjIFCSDc3UlHomO2HCqXR9WS8VHkXlvFK4/ECUvw+fyPP7bMgVjkJ2ozFKNVtc5Y7+0yEMpBhyM3dGUxs7Nm/cnPzZZmpLyl6vVmhbNoOPPPngfPNJuytUcerRUfzf4TqTyCCaAl5OzQVVxT34JEOBdtjClQo+Fmjgo+WARXh9jSFlULeiinkTR6UAi0xlYe8bQhlZ1ENcOXvgOopWOmfiGdKF2JZsi0th5Jmp0ItgV679Xm4B1uCEzDTb8ozdftYtEXRVHy3TsVd01WcVqKxAsTXnFVYlNKPj4DThYpECA/EK9GTBD5SpgGtO7kCa2Ms74LGepSHVeC+mSrK8ugtnobjzwMOO3Nor5GQkBgaobzqkvPR+N7jaT8vPfpb43mvx42br74E6174Mza/9g/8/rarUVGmh5x11NVU4v47rsPW1x/Cmuf+hGu/8Tk4nY69QCiHEvLWn8sV8hbhUTuFUg95Uz4j83mjXEnW0UJDXJ/bfGpioMqbEUp9P24P6+PdpRHBVNCRUJgCkdWHUlcod0SBFk9xXgplsVPDmwtT+HRl/iGhylyTMik5pKKQ4rAfGZtTyI+FJcM9nCSMB4WSCPT53wY+crm9cfeBiFnL+OJQd0Uwg1nvaBpKY70sp/BgxtkoBzGSEfIeqJQ25fiRIrfmZWDFKbY5lGkhbwHK2aXFl+iJLbZ3eZD47A+AGYt5YZA5x5BC2KZcTQp5H9f9AWZ6VfyiaYCsvRPmzhAT+1sBnylETp/TpFA2JQZe0xpLoYrlUA6c/6V6/+2OJafwReKU+ay96w5fBSZpYV2h1OdAjw9FqQhbAGegrxub/TVs0esU1kEeL5RkjKmS35uo4YvVGn45TcM7VG+DKiyKUSrBwHxT7HWz19bHFbzZBxxSQArlLv5kdaZKWaaT4asa/Shx8a49eYNI+4pTgaM/mrtwSmL/BC2kB3NYkNhjDJnJbdiyE4tP/JTx85HPfcd47oZvfhEnH3MILv7WT3DOF65GdWUZ7v3Z1QNv5nAwMulxu3DWZ7+FK679BT7x4RPxrcsuxKhBeDWaQ975KJTaICFvEQ6zaTXI9p9KsXzGZhbyThn2HlE1k1AyGw4aH5FKbwBliT50qnyMXSmgWAw9aQp50yRPN6xwN6Z6gW39SbR6ilHtGaxbjoY/zFSxvAA4PZ3r24KqR/8xO4WmFSqOKbQnoCyfi25+ljDYvg7Wus7hgNLfx8d/oOdQ0jlz7hXc54++qzkHY1xgznL+286Rwe2FLxGB1wE826Mww+/JtLaLZoa8jfaowjZIoGELr/a2hL1ZlXe0H3WuFBqWxXFkoU5saD7o68pQKFP0vdA+Hv018Oyf09/Dam7u8WMKkUZGIgceFkblVbFOS8ib2x2Rl+RMn57bPYhCGVOB8IJj+Fw4YTrz0NyJACa6aD6L8rHSXOcLopAIZcJmfujrYQtdSlElcieOOVW9UxceTQN+sFthzz3ZrWB13IvyVD/L8xQo9fK5sC2uYmWfwkk/HT8yfrfJo6xw8XGsmXMiHmhTcEmN7qGZBTRfH3LKmTiyrhxlB+nnCs3XR30k62sk9lPMPQSYf9hYj+KAxZAJZSqVQltHt/HT2c3DMoUFAZz/0ZNxw+334NW312Dt+q248vpfYsWS+Vi2kCetH3v4UsyePglfueZneH/jdjz/6ju49c4H8NlPfAhuc6eYUc6hNPfa3uOQt7jZ2CiU9Lpgop95s7HQEhFH3T4kps9rXgqDmwklgW4AvgBKkmGWs0SgEA95wPExmQilnrg/IdLBboY7QnE2cVdb+u5a8aUqDWeXASv7gGW00h8ED81RcVghWM/fCyuyKJqk7DFCGbc/HvsoVHHDpV7JsQObUGr0WT/5HW519dAvgK1rxgehpO+U1LUshJIUytII78v9TDd/jBEWm5A3I2UEc8ibQHZAtPi0KFpM/Y7248KSCLuGv1prun5sPCzF+XiW0oyG5eTdqOUglD5UxbpYnnVSG1hEthmEMr3IRvTOPrWEE7vHOgdeQ3nePi2JIr19oiCUHQ79eiAFdsIM1ot8VwwodGosLYePwwvNX4DCVBShhM18Gu5Gt4sfR2Me83jhi/XjkqoU/tSm4If1Dpy13sEM1NdE+UaLgwO3pjK9YKotquLtPoUprCyvPEseZbmuULZUzsQdTQrqaB1Vnn2uKy0I4IXuR/Di5FZs8L6Oio2vAq/+C1h49PhR8ccLKE1iP8vz358wZBY3bfIEvPvUfYjFE3hnzQb8+Ff3o6G5DYvmzYTH7cbLb642tt2yox71ja1Yvngu3l27EQcvmssUzvZOfeYG8MJrq/CT71+OOTMmY93GbVnf123OHczynN02iYISHjxxuuBxOtk2QqF0611p7BBXVThdrqz7psmf6KDi9qQ9J/ZfG+efsSPFw9/kF0fP8WaLSfjUOAt102OOOJ+cb5mUQMgZ4SFvchZyOtGr0kScYn8Tmdd8fExqYSl7/1kqL4bZHVPQ4ghgkZNvm+24HF2s4fUQ8PtWB/4wI4Uqj8Mgr9btfYqGJcEUvrbDyfJBr6hN4SfdWtp27Nh6fHAmYlCTcSgeH1w2xzTXd2SHvbE9y3Gjv2MRpOJRKL7AfjN26/bZ9iH+V0/9DFBWA9ffboWjeTtSW95F6syL4S6phBLqHNOx59puuPtOzVqKFOUPNm5li7CMa9XtRVmUX6tb406s6U/hmokanoiHEfUF0q4loVC61BQc5hSavk4Qj3OVVcNBljqsdseDuNuLgngfPl4cwe64grNLNUzyOVgRTDLUCa24Im3MKT3EfkGgl6XL3DNTw4c30vMKktEwtIo6Y3vNF0BltBkdScUYI3ucLULjqEEfW5yKOS/l8sCR6sWnqzSsDivYEqf5kL+mg13/SdT6nIjq21OVd6e3BI4Nb8OxfR2S1EHI7cXudRvYa6ZrfaBP6vYG4AwWoShZj/6EJ20sbDzJOLrAb+A01+xKOJhye0rPOvYZf9dK41DwjF5/1BBNoafIjyWlDjzbm2BjKdUJZXdCxeoI7V/F4UUOtLW+i5nlRbjf8p0KhbK1dg6a42480xPHFbXAI1321zblWxI+N/di/GLz/fjuzsdw9cYIEidfBGfdTDj17zTbOTaU89E4LrTQURTDp3So+862/Z7eJ4ez7Whsb31+pMae8Bewa958no71ZzVjXxrLULbbI0L57tpN+Pp1v8DWHQ2oqihlOZWP/uEWHP+xr7D/iWT2htItH9o6u1FVzmOrlRUlTNU0Q5DLyopSYGP2964qtPd6G2yb+sIyJONRdgFPKCllLcB6dePxuuKiLJbEwC5FQ6E/gFJ9n9Z9h0vLQQEnt9ePupL02HG7w4m6JJ8hFX8RSxJ3q0nUlJQg6KFbT4wplAGnwvYb1/OszihMoMIRwcZECTrhRF1JERRPBEXOECaXFKOJ7C0dTvaa/spaUKbRId4kK+CJ+0vQoXhRrcQzxmMe+2R/F3pUBxqdpIZ04qSqIF6PeGy3P8ibgFPpQouzCBsTCq51duL4YAz/0wb2p9JN1uFAmcuBXi0Fd0EhKi3vP9h3lAujuX2/rghVOIFWNQl3QdF+M/Zs22fbh7OsBoEda1ER7QJKSqC27cDOVBKFi49C8bqXRmUsI7X9nuw7Vl6H1pM/i1RBKTxtu+HtakSsZnrGtdHh9qIizqMs3kARrm3T8ODkLtyqrsUV3jPSto/pCmWV3wuv6XFNUbFDVVFcMxlF3Q1GsRdl+V3kaESRQ8Nn6kvxt0ld+MokD+7qDKIzFka4blba/kO+ArjUJE4piOO1fjdOLE7ge1O9uK87gE41gXCwyNi+I1iEyvgm9GiujM/UpXZgIrVS9PoxoaSEzXENLjdq1Cg+VKLhZx0FqCsZUF8VNy1NOzEl4ERc31epswcdniIUR3pQEG7HbnowUIiuCFch53uSeIuORXkl4qXlTKGE4ssYC/tcNEEBmFEcRJPbi9ZAEFOiuxBX6TOXoM43MAtHnQrWFkzGwcXNqCvh12e5W0NCccJHC9dgKZoT7Tih3IMTYq/D3+rAs5b3LHdF0O0MIOYrwsRJ0/FYuAF3TOjF4ZUF2JXIvOWVuPj7v9cawh0lh+GbiefxYFE53kwlUVJWgSKbz7Sn5y8tYjuO+Cj6py1i5+WEx389rH1bt9/T++RIbDsa21ufH+7Yd1GUgu7Pw/xOR3v7qn1oLKNGKClELbB+8w6sWrcJbz1xL8465ShE9erl0UJrKIREls42xKLpANltQysS5jNYORENoRA80OAj1p1KobE7ndyakUom0RuPIxEK2e47NYH/nVAcaDDthymODicqYrxScU1HCMlEHKlwiG1XHOCTlz/UhkgkyfZbpveuLVfiqFKSKO7dij/0aWjoTmCHogI1QF9fN2LRCJxFFbi0sBNe12ZcAWBqshMbIwq2d/WgOeVEuRZDS08XC4PZHZeiiUm836/gldYQ+iYBk7QQHuoeWLWYtz++IsX8LV9s7UNYVfBOlYIPF0Vxf1OCPU/bl1VNYK/t6u5AKtoPSqMyHw+774gKkxIX3wrXE/fCsfODIX+nI7W9XyeUHe3NiPf3IQ4H4oOMfbTGMtzts+1DPJ5weZEMdSNm+nxK/SZ0VUxGn+X83Rc+q9iOsCf7jk6pQKqwDM5n/gxt5wfon3soUlMWZFyrisuDIiLZADZ2hZh6+APFiZsmb8ItWj/qe3pZNTJtW6SbvLZ1dUKxniehTnR5ggjpjzsrOGE7R6vHy/0evNAexYMBBy4qDuO/rTHsam1AauGxqO/pgaJx1d/rDeDIjnUocmr41jYN51U48L2aPjgS/fhBdzuS3oAxflVxojLRi6ZoKuN6a4ypKFJ62Y2zIRyBhzVO8OD03vdZLuM99TE0mfJAw1SAMw0oUmNsX0yhrNPQ5i1Cb30r+hp2sOIaykff2dSASBVQFuPHrCUaQ6GmwQENjb19aOjOXKJ7IzxhMxWl5yNIKU7me9maVNDQrduN6dAULzbNnY5Fjl1sWzbHOAvQ7i5EU3sbK3J6M6Thk8X9YCmpCaCj142oOhBlKa9xs/QfQrOvBH/ZugW3VANHunrwelumgl9cx8+zxndexh0dzbhkMfDb6k78dtd/8aeUZnyn1nNssHPSui0NN3nWBdAmzoXSuhuxYHHG+bin1xJhsNcOZ+xDGctIbG99fqTGnvLQdamO2HEf6e3d+9BYzNvni2ElLpIauW1XI6ZOqsVLb7zHqryLCoNpKmVlWQladVWyrb0bSxfMTtuHqAJva9e7lWQBffj4IAcgYxtSz3xBaPWbGaFMQGFhZq9ehZ1zf2qK2XCIg56xb2GZ4XRn7MfjcLAkd1qBt8RT3O4n1s+260vy3CD/+6+CotW0X2esH041hUqF51R6tSSr7qaXtull4UElhdZkAg6nCycXp1DtasUV4V4s9qewKkzbptCScBi9wJt0Q2Lr2KtcGpriQDSlYlUYWBJQ2fvYHcf5PhXbYkCXnmz/RJcDl9cSmYSxP+Epl4yEmS0SVcLmOq607wT575FyXFYDbFub/TtIGzsdh8EKjvI7TwToBk7t35I0bgo9+QsGHXu++x6r7bPtQ/P6oUXC6c/RQqus1nb7femz7sm+U9SNhVIZVj4N9spJPawYyboft8eLYt04nKqd45qCf3dquGkyMDnagUbKPdS73YiQd4L5QlrG090GtajM2L9LdzuY6IjifzEPEqkkrt0FzJoNPDM/iYt71+NepwsJXyEvMKHX+IL4UNtKZhX2VkjFmyGgOabg5il0HW7E//nOQ5xWeJrKUm0qQn14LzFwLQq0xDVUeniFOC0klAhdlx4ckmhm1/xOURmoozWlIQYHqhwJY1+UZ7nBXYhUXw9LtUHjNmD2MqTaGtFQ6sRkvd1r0ulGkHIvVaAnoSGeysyzjof7WapPoYPPNYrLi6pEiBUQZXyv4V50ugtYDqd4rsyZQqu7CIloM5uX3wqB5YG3qG5UOxKo8zmwPjRQYFnudqPVw3PMk5V16NnwFp7oUvCR0hRurrd3vUhBQWc0Di2h4mMbHczL87c7/4Y2z7H45zCvD2Pb+YcDc1cAj94BjSr8jzx7xK69obx2tK+9kdze+vywxk7XLxWNqgPn1miO3Yxo1RREli+AKtqG7uPHfU8xLL+egN+HKRNr0NrehTXrtyCeSOCoQxYbz8+YUoeJE6rwzmqed7NyzQbMnTkF5aXFAwa0hy9hBHTTNt0GYiQR1DtOCN83vaCFV2HnqPBmG2mD2AaJKm9726DqZC+v8CYStPolYOPb7DlhG+TfvhrY8h77WyGLof42ZvexG3y/naIZhz7MElpYpxJwOhTM8WmoQhxzuzZjYQB4LzxwI8nVLYdUBKpibdHFiXf7lJyFOdQ6cq0pg6E7Bfgt1ZKsUpp9ML3KO5+EZ+EdZ6pCzQXqid6+QmXt8UYSVJDhEObKVNV5gPpQaoa1k8XChqpkxTUy1qioAyhPb6RA+bFmU3HydKTr32IFRD2uSxN9iKi8pzWBNSOgxVfcWthiYxskQOb4xZUD/+vndrkjha4Un0ca4gqOXefAcz3AR5y8Qttc6a36CnB69zr8t4sSc2gsCm5tdODfncCXHbvTiww9flQkw2i3mcZaEwqqKOTNjoPfsCSaoIZRbxtIUtCq+FGtDHyuEpfGiJ1hrk6RhO42KJEQ6pNOTHHqO/J4Uejjx8XWh5LQ34MuZ2CgKMftQVWyz6hIT0M0jC5XwPAFZcdQSTKPXVFE+VqIf0/fDPHoyPTC9DmnwqlxhZIKmfT2jA920FwHzDC3gNRR6lTZZ9X0RhOvhBR8eIMDMUo7oop2CxZ4E3hybgKuHJXjtjjxfOCDN4ANb+vG84HBm2dIjBzEtU/3dZsmB6MFjaJgR5wDldo0k8+swJR5wEXfw4GEIZ3N133j8zhs+QJGEg9ePBd/+Pk1UFMqHv3fiwj19eOvjz6NG676Ao44eCEWzpuBn994BVauXs8Kcggvvr4Km7btxh03XYn5s6eyqu/vXH4R7vvHfxBPDELwhmMZZCGUwng8J5gPZa4qb+FDaWds7kRNss+4MWHlU7yq1mQbRJXZZtT2NbPf93jnGXZBgsQR2GScTGJGogse/bWfaXsdASdYkj2hJaarkFmulXIX4FTIykgx7EZm+Iis2kyM5ROwoMiNtf2m/CYV8LP31tJ9/AQhozBaPsbmQySUxxRpTDFJa982AuBmz/qXdADbBjFljc59UwGAQbJEm7+xxjHnAiecn//2R58DLDsx+/PkqWj+vIIYWT4vKexEKMXCjUAtBintr5q1IzSZg4ubUDLOKrDTrhtSe00m21Q041ETKHRo6NKL3ggU9VgbVjBNEDIxR5FThseBefE2RjjNuLfVgRXufiwO7RjwrvT4UJHqR5vJT1KgLQmWOsOPQ8A412u1CBqp0YINWuBBFQZ8L0scKjpchQNtH995GrjnGvZnQ8KJySzvksihD4VuPq/a+lAS+nrQ5Qqaqrx9qEqFGfHNgKahS3OjRCFNkx/fciWBNufA9/ByCJi3yoG/dXsQcbgxPZAeaKtwptDiLgZ2b+IdkgD8txsIp4BzyBTdAvqsnURY0xYKCpqdAdQ4MlnvUn8CRxdpOGgotrXBIqxa/2O80XAvvlytwkXOEgS79p4SowOzS8JebMChTV+EOC1siFOYnTXIfWLSHHsOMR4IZW11Oe788Tfx8j/vwl23fgdd3SGc+elvorOLJ7XfcNs9eOblt/H7269mxTqkXH7hypuN16uqik9/7UakVBWP//E2/Pqmq/DQ48/jp3daPNdG2tQ8Q6F05Uko8/ChzGJsTitwoQSaYdgG6b1yBWp1T7kHChbikcAcvKGvwg2FktS5VBLzmekvsMtZhM/3rmJ/v6cLMa0R/oZVdtZBReWoPufLfDt9jnxXJ6LLbHhd1bKjWDjJTCj7hYem6T6gUWiRfbBo/sbmQySUi/TNyP5jJEEEgbW9FIT4ACWUhopsVSiJUNJ5PNYTGk30M5fwm2uuRZwAbUPmxGRYng3WLjWCUOr5yuYFEdl0mQklqYNtKZ62Yr7hC9sgSpN4ZaGKTctUfLVGRQVdm2QdRORQzAe+AMrJuoctCtPnEUojmepRWW6mmbCKji5W0vdEF3/s800vGNdOwO1EAMksCiVQ5UzxKIs3wGiZ5vagBtG0DjlmsPCxyo8XeTYWKil0kEJJKjY7KJT4zFXPxoQDU9z6ZECV7Hq5eK+JOKch3INuT2GaDyWRYVuFkhUVOUB7LNRPhQrE0GoilET2NkcVaNF+bPdVssYOZlQ4EsyTF7s3AqVV7LqOqAqL5MyzIYEljhRXYy12UC1MtU3vN872r9sS5WO7JlBTWYWF4Xo4UwncMU3Dq4VrMT9cn/ccKDECMB/rvWgdlDryI/A2bYNj48p0QiksqSz2ZPszhpRDeel3f5rzearyvubHd7GfbGhoasOnvvID7NUVSajbQiipXHowQqnlDkeIkDe7ydBEaupVSwplqg+rbVbgZBZsJWWEmkgHy+PZHajGJ9ynA9EtfOiUgqnxkDeRn4Nizeym8ET1PFzS9SZ2Uo6jni8Z6+9HT5kf1X66y1hymWqnobq0lGLqhnK6KQL0pfjE+Fxv+oAWFThAziNrI2aFUi8ocsDotqsKI3PhQ+kZAqE0rxhzYFGAH9uJnvzyKPdIoTyAfSgHCKVFoQybVDux6Bqr7hWGvyrlFKYXmaTo+bJarvI3bAbqZnKiZ1L3BieUvbZelERuSlIRdCdtSJnF7JuFvFUVy/wptrh5qhu4faqGn0/T8I/+93CBOLc7GgFvEFX93G5GhLwFtkcV+BwaakNNaDQR1jIHv2atJJHmhftbNVzifwVXFZ/E7MIq9PB0O5tj0olNS1xhC1bqXtNLCwanCy5NZQ4QjXaqIL0m5cRByT5mZSM6c3U4bdIkyDkj4WTksDjajR7qkuPhL+jL1niLhbGDKGXEU2M380otYq9QEgHXPz8pmk1JsELDdsXm2oyGsd03FdO929PSesqQ4CHvHSv5g2dfBjxxL5oTnag1e3vqIDW00xVkESAzmjUPqjVTtyJLJx5aiP8f8sOick5mztsAlDoc+NPcJO7ZcDeOyJNQHuTX2LzdbsqNlxgOodxLCmVhKbTaaSh++j509oehnn05nyMoomEQSj9bdB0IOLATOOiLop6zYuUp1A9WlDNYDmWerRcJVoWHcihT4YGQtwkU8qJUR59l1zXRTrQ6AlCJZOlFAGwYUNCT0kPepFBGmvB+RMFrJXPZ8yJ/kqE/xM3N/TaKU7AY1bo3phgXjYVeb1Uoacpd6Imh3+HBNqUgQ6EMmMaukkJJai4d4yQplEMJeQ++MiO1RKgKk7yjqVBGD9jWi5r4XHYKJWGsw94LjwJ6O20VRIJ6yOmsgAGfvpZvS60JCTatFA34LDmUlE9HiqDls6puD0rVaJpCSWiNa6hK9Kb3w6aQdzKO00s11nDgrA0OTH3XgbuaFZzl49XgKOHnthYoQEU/J+mdFuWOFErC9FC6QlWm5w2228wblDdIxLeygG9fKQilzTRGIW8CGZ+z8bu9qCFyTO3Es4S8idzxbjl+QynttBBhgYYkn0en9DWxfRf6PLlD3rEIutxBw08y6ASCoCJD+81F/nipUyeIWgxtupdlGqL92OavwjTnwAGr0NN6WiiE3bobePDn3Mz/czeiCX7b/HJGKJkCmk42m1MuQ7U1Q/hcUm53vlhQoKDP4cH2SIq1x/xLtxeTo9RvfXBCeUKRhrcWUd/z/N8vV2egvQa6L+YpGuw1U/O9rVC6+fs4IyEoVIBK90mhUpJ6TrB05NqfcWATSiJ9iehAAY6pKEcZVKEcpFMO3aSFumVZ7WiKA9WqPaEkUCWptUMiGaE3U86ShVAS6GYnCOVB/Y34IOLAq5X8pvqeHrZmCPeyUE+V3qosg1AmehDSHCz8I0CTW0boJliMo8Pb8HbhDKiBgQIqKlwgmMkwhdIYaWcfjIpy8iGUevGCqddwNlABEuWMkpI64iFvplAmBwglLSBGYeUqbtCjjVj5BKQOOnIICqVOKEe0MEfDBA8tg/L8zFTpT11YKM84W3tEuum+9jiw4S2eOzlrKf8sdK1kC9eL/vLGTjSAnAgs+6cFUYkaNcz9BShdpTrWnVmUk0zgtBINT1P7d01hoWiqIKZrojbSnnZuV+odeKwK5Q79cpnW1ziQ40j3F50kUvebrCQx6GXzWCViJoUyHSKUXB1u4wqr24sJcV5JThXkdqCCPpYz6gsYCqXdOAgNupvE5P5mVlRUqGiIag42r9kiHmEKJfN7VByoUvn3kk2h7NJtJ2gc9EPtE9o0m+tSTWG7uxTTHVHjfBPpPq3Qz/ktq4A/XMvmzpZ5x6DGpjVtKRI6oUxHa8qBGt1P2NqJh3JsKRWHCnOCDg01bg1+SxqTGQvcMbzvLNOLrYCWSILZPjn8uRbVGs4s1fDwXJXl3E/05ndNfbhUQ8cKFYcNISQ/KjjiLOD872Kfgfl+s7cIpVNPk0klWKoMdq4Hpi3gc5dYTBxAIe8Dm1DSSRM3EUr95sOqvAfNoRysl7dvQOGx3NSKkYAXKpqzqAFkJ2RVKGuTITRTmIZOMhtCWUwtc1MxzIy24v2UDzv9VbixfwL+0m56j/5etLiLUGXXzztYxBSIFstK/90+sN6+ZJ0h4KyYgOO6P8DTZQvTFB1BKAOmiZOqZCm36vqJKr6gbh30QmXHvrAURZ31ea3MFujhbipU4CHvkQO1sUzLoSSMsEp5RomG3cvVQVtiDhfqhBlo+vBXkDr98xmkmDqTDFWh3JPREtHaukzFruUq/jNPhScflWTOCn6Nrn1ZH4uN5xmRLlIYX3yY2U2xinCqliUUZFEpvUGbzxtK27/ILSzV4pkKJYW8GaFMVyjLo504pACsEjtDcezYaqjvpFBWRjsZ8QiZFnAidYRamU6PtAzsXy+y6dRcLMRthWipWEnRh8qJqKDwtIloWsfOtg2382uM8ifps+QilNEU/FRE5A+w4j1CB01UNiDlkj5XbaQDqJrEQuthLcdcGYuim0LeNMf4AlwJNX0mK7pi/ENRWJ0UR7atap+dtc1RBL+isk5e5oLEFjMBpXDiP25Hc0E1I5zW6uwSxNEp2kyaQPN3daIXimV+pxzKN/v4IuLMUmDHchX1B6uoP0TJSioXql1Ymxw4l1oiSUaUy/UKeSvIi/T1hSr+OVfFGyHg4Q6gNo9U54+Uqvj7bJUVa07Jk4COGqqnAJV1+eVF7y2FUtz39xahdOmEUggXZGFIC2haSAuMgEKZPOkingqUB1IePxJnXTYqKV4HNqFkKkV04CTST+y8bIMGK8qhm7RQeCxh3io9TJJtwqSVvLUoh0LkTb4yfoMhJcUE0c97rtrLQkDvK6Us1+nG9kJsjZpuPpE+rlDqOT5pCJagKt7L7EHMIIWSYA57r6gIoCgVxTOlC9LUKxHy9pvmB6baJGK4tEbD55V6fgHlIuKFpShQY9ix9lp8LGxvam61LtoeBT7oVzBxhOcAslJxGDmUglCO7EX2kXKNqQvUD33UUDMVyY9fBRedj3TOVk/NT6Gkc5zONYtCSSpK4pLbgYMOZ0T4zukqvj8xW4LcAKhXNeW/fXWbgmOKgD/NoqSKQW5qFP7ZupqTPfourDmOdC4xC6Aw0NnEiSeNWxDQbGFvuvbNIW+jqt20f7puFQcjFNYcSoouEJmw5lCe0rWO2Xs9aTLwNhTH3t0DeZ3+QpTHe3WVL5Mg7ogC02KmkKe/ABWJEG/VagMxl1S4HUDNNFTGehhRtVMFiRyTdWxVtJP78JJlULwLCY1XsNuhNcrfgNJlhKLeHbXfmL5VOj4TKKReOQlFyQj6KNE7G2L9PIeSQvreAM9NzaFQ9kQ56yWbsAp9Idau2h+XbeDHb7p+ihsKpWYhoB2NaO4N27hg8JC60bfchOaYCreWQllBuoJEx+eZHgdLs//DDJXNz1fHpzP/31qTJZ6Aw+PF/GgL1kZsVGSr3YeO44qAFQXAh9Y7cPp6B7ZFeQ/zbChwaPhJdS/+MiuJRzsVRvhFEdSYgXIE6V5rcj8YU5AqGNL9rvOMRJHyTPnOwyaUKf0Lb9jCr/kZSwa2GaZCSaNTlxwHLDomr+3jFROhkR9q5USMNA5sQkk3UlKeBGkwbIPyVCgHsw3KolBS9WWuJHXyu/Nai3K0fjQHqjghsCqULIdSw4JoE/v/gwl6Dpl4f2PMKZaHSdXZGSigHMoetDjTw8zmwhyBk4I0wfrxrn9i2g1YhMr95ipvlwcz+xtZP9wljhCzSsl1sVL/4kN7t6JIi+Pk7g8GvbCJUK7pB3bHgQnU5XGPtLM8cyhHnFBqOLWEj/fw0Qo/lVQCn7gKSkcjJvzzFzztgFbAVkJJ1wGFfa2wsQ5iaQxFZZi/4gisX6Li81Uarq7TeDVzVmjsBvhIh4Lftjjwpa0Kzi2n7y/7Kz4+qQBLChSAqh9tFEQ+dn0BJK6JZ/4M/OUWXIbtOK/lNdvCHE1RuKppq1CaPqv+XVMOnVWhpJA3hcKpWYMxFpcbK/p2YGNkwHorTXHsbzLIuUYEMd7Lem3bYVtMwfRE50DIW98+W9FFWAUimsKKWTB9ISp7G41ivIzPT1XqZB1EhI8plF5G/pqTpIllKcrp56y42u9iYeYupx8py8LWDMrFpDQd2n9htAfhbBXephzKYocKh9fHQuupHORWjYRZ68RSl4JanSA2ZSHa21N8lTlNV+OILPYqHkT0ZgxmNEf4tW5W+qj20A0Nncich1oEyQ4OzAkUnaEQ9/YYsCECFLmAy7Y58J8gz2mvKskklDOrylizinVdAwU+Ih2q2i6apFeQU/ElX7gorBkFH7f9NfiVGhWnF0Zx8TYnLtyssAUS8y4eK9BCkOYmQplefDLWICIX6hySQvniAhVfqxkJQpnk/zdt49xiwRG8+JDuO8NUKOkezLgKWRDlgZSYY0fBYWAcEEqbHEpnHoSSEuxNShvL4zITzBwKJYW7zSFiO+ug9JC3hhrE0OTVb44ZIW+FrTYPijZju7ccPYtP4k+I9zehxeFHpRLPVIYCRazdWYvbcsO2Kcw5Ea14zjWBTey2IW/TYaCb7CHkj0efW9GwuG9XzouVOkQc2cN9SdnvQfIoF/g1Zl1EptAkzrCk+lM/C0zmE7jdinJIOZSjSCgX+jWW90lhxkNZn7hRwIe+xG7Yrod/CUciCqVlBzBheiYps6qTZkJpUSiFonl6YjccTgcWvMdp/Geqsn8GSpsgIvJ2H79BPtvDf0/JciqQynNfXQg/2vY3rlASyPPQausjJltxTcSjcOzegOtq47ig6WV7hdLGJol8IxW6XsyE1eNlvbMLFNXwexVo08maWc2iiZtCzXa50aSiT6N2qyLnmBTKVBidWUgfbT81ZVJAdYWynWREW5CVkROV1HecCGWoJWvRjFDAKvUqda2ghJE/IiXZ0NzHCSXlX9OxavSUMhPzrNuTQkk5lxSejXaz1qxZkYih08U/Z4nfyyIlnaqTzT22iPShk4p4vC52/XQ7feizIYhs03gcTY4g89MlkKLe5gwOpLCkfUZ+jYvwOEF4Y3YpmSdqcz//omv8A1JfpQjBJxT8qU3B7Y0KnupR0FbK/S4rizLns4PK+Gdf2zzQDc4wz8+ySFsa1FhXI4EmEu+dFAq33RyHF6p4o9+DP7XTBgo7n4tHQKFUqQDugu8Cl/+cW3vlC1IlhYBTagrvjnXImxxf6N6eB6GkwqZpXmCqbyRyKJMD95m2en58ulr5HDVMhZLywH+/4W6crLTlVWCZEnPsKHigjg9CKchjWqecoflQJi76PrDiVP0/Jb3U36JQ+gYhlCzkbZpLSxwaI2PNHntC2aOvNg/yq9iIQl4dRtViggSZQDmSLgrjmCYTzaxQivcwgTwvzyjVcGqxioO8CayINuCZaDBDvTKKciwK5YrILhbCI+X1kN4tgyiU5Tiy832mds6NNKEikP1qJVJMN/TdMaBeDytOpAO35Fhg6kEZ28/0JLFlSQJL9LzLvHIohXotvstBwjM0pu/VUc7W4O9xSonG1N/fNClYrifwjyRYOJjI48qnjZu/QivgWiuh9EHJRigZybJWPvPvZGH3FqwLTMSWqAMPdSj4UnX2YpsVQX5yvNU3EKIlI/zJWfK4LihX4VVUnNj1Psr0Ig07hTKlT7beaAi/maYysrO8gEK/5IzQwXMqrfAGMLu/ET/3bMYsn4bLa1SW23lB/7r0HEq3D6VJfq1Z1T7hIWu+4bMcymSfbRU2hSSnJ7s4Oaf5hXwoKScyiwq3LQpM0CLw65Y7mgh5680J7EBtWGkbZrsT7cxJKOn4V1NBCR2/4grURjvQJDzLbNCV1BBXnOy8nuvX8EFw4oB3ZzaFMsWfL4r1oi8XoaTwuZ4DWeYjQtmDjhxjp4UFK+LxuljedAORW9HRyopoP3Z5Sg0HiEkeYLe7BIoNoWzt7WMkllRYgXJR0a5lJii29PF9VPsGtjdC6gngp40OfGcn/xwdFVPZvqtMaqbAgqCCBncxa+0o0K8q6FPcqCa/UBssDYK11BUQ1fkTbKZWuiZXEAGNutPuGZR3P1yoBx3BCSGd08JdIR8IVZLuZcIeZ4RAn5e09iGDxAsylM+zAQctZii9ZSj57wXW8Lg15C3C3oSuFp6SN0yF0u3x4HPNL+J3G++Bf9LgeZQpMd9LhXJkFMq8bIOsIW9SQkQoUXgtipCz5eT08e7BRlccK4h4mRXKSt2GIhuhFFXe8/0aNlPsy+whaEGbxseWZo/h8UNxupgy0OLNVHRualDwQg/w6Jwk/jmlC1v91fhXh5qRc2bYBpkKeEjlOyRaj1dDCt6Le3FI79ac1kGuwlIc2rcNf+jhF9HhmREiAwFFYxc0tXSjkDehrkg3v7ZZXdW4Umz7D5Vqe9Ypp7OZJ5LnwGEFwA8mazi3PA9CWayyYqKXehWmLizKY0FIxVFT802mp8RuOtatA21LHUQoKdRkIolMccylUFoJpa7wLezYiNUlM9n+7m5RmAp5Qpbva0WBxkLBolqaqCctBCbbCgEaPjfRg+dL5sOhqfiI6F4SsQl564TyIl8nLq7RcNWEgTSCWlLIbELeXp8Pf3//l/hqsAPrlqj45TSN3X7mxNstCuUAobTLoSRUO5Np50t5st82LE0h0GlaHz+W+nuUqdGsIe/tMf74VK1/QNEkQpmlEIbQHk+hUi+uIWKZW6FUUE2FO9TDvbgCE6IdaWH6TChodRWg2qVirh9YH5wIxZpSY0JTggglP3ZF8XBuhZKZlfO5t9TrZCHvnH6KkT5WxFPmcaLOo6HeW267eGaIhrHTW24UoEzyatjtKeM3agtSPZ1ocxeittCfoVB2IpNQ9vdHEHL60irDhWKd1qFIUaCW1aDdXYhKE/kUmOJKYKsz88Jhxuk26UlE6ok4isYTQqEk2BXmzKFuZy5gVcREKFMjk0NJPq1o3gHseH/QuTENREJpbiVz+REOeT8wS0P4MBUfLEnhxOIhEEsiUBR1y7NFMC1OcrUytmKqV0PLChWLzYKGNeRNaOSE8sTOtfjvtruGXQharZOJybEOfLc6y8LLVqGUhHLPCKUlhzIvhZJkcV2hZEoQnYBVPKxhnAA04WoajvDRl6hlEMrsCiWM9olmQtmUjVCmeDiRVuHbOkI8Ty7LZN+iJ6OnXQQFxShP9MEFFS2BTAUulFJwzkYHLt3mxOV907Bwxa1o6+3jCoUpHEo2KZTsbc6hdDmdWBJvYcrUmxE3DiWFMoe5+SJPHAVaAn9rU7DbW4YjA9mJfYFOXGl8lG9FBH1SgTfrxVCkrw5Py5dQshxK0/u37Bp00jy3mh/fg+oGmyQ1HFqg4fkeBav6eWU//T8Yrpuk4dUFpN4Nvq0qzsc2vc8zUyh1k2dT2JuHvDP99AZC3ta8RR/cahLz0Iu1BZOBigl4LcRtZA7O4r1HCslberhbgBYBYlK2hvPmOSP4sXM+XuwFPi7Ieb9dyDvA/B2vKAuz64nC7h8t09h5SO37HKK3tQk/ruzBrP4WHLqjEt/aoeDirQre7gPqUn2cgIuQuIfaLuoKZUbIm/+uUuLpCqXab/gkWhXHWiUOv5bgJuxEKBHLHvIWhTypHrZA0vxBrlDmIFpEYiqjXWyBTLZBuQglhbdrqDiQQt5FFZjAQt65SV+LI4h5jn6myHwQrBtEoQSqtAhLGZiu9mB3Ircc1qUTTkYoY105PycRSu5byVWiel9FTkK5219pUig17PIRAbVZQPW2s0W72aeXctMJHZrN+DUVze6itGgEKZRUjJPm/1lUzs6rVmcQlTY5kcVIokvJvBBa4UWVbv9khiAkaSFv/TSssXG6OLRAZTmpa6IDDJIWSGbnjj0GiSVEwIhU0nyTb+9xIpHdrUBH86AKJeVmf3OCyor4zspj7qa2l9RUgI7Jg7NVwwkkr5A3KZR52tsJm6Yqm0VCtnF5HQPOJAahJC5hTrGjSm8A1ybX4OT+rSg2k4E9QK3+UR4MzMM3k+/jB5NU+3bKOlLCG1QSypELeStDaL1o9KumUDOdiEKiDodwfPcHeKl4PRaY1Ce/lhwkh1KBz0QYKvWwByOUdPJF0ydDmhxIeSNsiQCOTSt5Nw4btKTcGe0XtQC3DCK0BnUzVQtIUfpjuxOPaTVIEeGmScSac6YXIJirvBckO1jOKJGJt8JOzIy2oFxvxWaHI1MtiMCJd7qieLV4Do70hAcNH5BCSQpKfRyYKPr22hFK/SIiWxdxo8jHNojsTBiBa9mJ0vJyHJ0131HDRyv4F7GgOPcKl9RVmidI6aJjtro/v0pv6ohR7QHOr8hj/JWTcMmWf+IMn+kYUscbCt+bCnOGGvKmUPCc/kbmlbrWU836urPjT/U+Nh+b7IGoeOotZyUw/zDj8Z0xxTbkfeSkcjS5i/H8q6/iwXYFxxeDqZSecLeNQunHae2rmDr/uS103QCLg2TbQ22+NFToptoCfkXDxYFO3Dj1HLzTk8Svmh2sF/bumIKJhhqoT6hpIe/0MdLiqZ06pSCeli9coUZszcSF4jgt2satUhihTGYtPKGQOhETZufjC8DtCzDj8mzbEyjUXkHXcVsDuwnnIpTsWqHP6/XDVVjMxi1UrmxodfhxbKqZ/b0+UJczh5IUSnr3WZFmTHLEsSWe+6Yr+pmXuBysQr09mSvk3cd6a9NNsc4LNHjLjLaPtgplsIYtXOgapvzIXYEq+/O9r5tZs9WYKqvJIikBB1u02oGKGKtdqbQcSvosafmfugUMK4RyZH6BJUig2y6kTueXSPcwYUlQY4s36oJmDpH3Ju0VSlqovt+voF9zILX4WGD6IvSkeN79YJjp03BUoYbZvizzDd37BKGkv8v5Ymmw3MPPuFvhontUF3mVVuYscL2iVsONkzQcV6ThtqlqzsJLyr0m9ZbyV6mxwNYYRdbycJMgIuwL4hepVXho2z35KZR6akS+Ie9D9WllqnnXundt2tnV1YLFD/0AR7n49VVrOr/2BDV6G9RLeyfhjrpT8Y0J3HJK3A+tSPlFyHuc51BSdd3bi1Isx2dIhJJASpQ55J2PsbniTLddoZOyYuKAwhHuwSmda9if5nwVL1JMo8yWXx9X00PeRGjCKSDm9OhWJ+kv7NZX86TKbEu44PzvvcDjv7Pdd18ihX7FxRTKS6pTuKYyBE03NSe0FFSxEE3OijEC5ZnYhEOjFoVyWbwZcTiwOgy80asZVeLZcEiiCe8oZUyxey0wBcsdoaxdHdIJJc+jNMzNbQhloUNl+6VOGfmEQkTI+99zk6w3c2nrVjy26U48Md9+gqLOGFMcMTxZPB8HxVuzFgYRxMVMEzuBlEryaRxMeaSwMuFrtcwlMff4KybixobH8cAsFVN05YK9W0dTWi6ouSiHrp201SsRSrouzD2rPT4sDHPVc23MpRNKHnajEKQV87xJRp7fnn8GcPJFxuPZQt5lbgX1rkJoXa14sENhSsxDc1Q8m3rBNofy4vqnmMJIeZwPdfLjeV8bv4CsrfTIdJoWX+8WTksL81MVdp3oy6wTSs3jG1ho2ZAtsp4hFU5cL25FQaGWyJJDyX9Pj7Qyn0xyOyhwqFmVOPKaJCscbiYeRLmXz025QsGUF0kh75Jn/8iKM5pzkLL6uML8GcucKdQEPAYJzAXKv67Qomye2RyoyalQUlEO4cSudez3lnhuhZLmpSQUpjpWM3ukHLeeVBLdDi8jZ9UuCnmXQcmqUPZjl7+aKUNUWEjf/Y5Atb2iqWlohg+1ekRIdOOhiva0SIX5c7J+3gNfOC3U261jJwUulURrfwJVqf6MG3WxFkO31cZIb3dZpWYuqJcEVKxiucjp3xddf3Y5lIcUaMwXM15chdTJnwKOOZflUGYr4BH4eDmFjVW8sEDFe4tVdn/NSihFWk3NFH4fFPdSG5xXruHerv/iovY3eJ6gw1TxnaWi/clusCgZ2T+dkaMBFi0sCev6FZZmceNuB+vlXjlYWNoXYOk1n3S24OS+TXBma4hgwsRyHjGkrk5m7+VsOFQXIqaY02hZd63MCeOy1GaWX0+Y4MhRLZcHiJBSKkd3/TZ8d+aFWNo4hR2P38+g81zLq8qbVNVv1KrDzvPfrwjlbD9PVs6uIKWjRovhytQGflBNhFLLq/WiKeRtXs2Q7C8Uylg/y4MgmAkiKZQRFkJRsoe8TU+RGS47uUiKt4S7zeG4rVFe0KPY2b8IJGKs7Rjl+lxUoeLYYJyFravIhJgmMU9pTql7gFDG9BBkQdrqkqxLzDmU1BGoWfGxce3oCePJkgW4rrAla9J0XbIP2/U8zy2OYqZumasurQSRQJOjuElOdiVzEEoNjQmabMhke+BxO8LK6JrLg4nJHhaCpfPqg7J1OKJ3M+tVbpc385EKBa3uQtzVGUBxKoKJy46wH7iJDIux/1+rgnI3cuZeEtkkAvbnNoV14TgxR34pYXqxH2ValFW//2EGN0pmICJlysvhOZT9TNWiGwfl+Tw+l04qzdbcnLZf1LONFVr1dnWykDeBKu3JuskKscLeMvUQvh9SbDw+7Jq8jN0ArQbnZYgbvZkp5/LwtU58fbuCwx098FHLUzO59QaY6v0q6zWv4NpdCr62XcE7evFPLYWxTe3dynWyQGobTInwTLGjc4euHbG9x8uKVYggJmz8HFtTRPh6jXOtTA9/24WxiWBRRGJalBPK8hg/rrlCu0QIGaGlAh5dNbMjqwKkgBFhXtTNQ2ZbiOxnARFowsRYJw/1M6Nu5ESLyr/crQiyRWKGj6cJInx+YvNKprRuG0ShJILX5fDhYHSjVI2gUW/fmA1dmguTlSgjiEyhzBHyZiFuAEcV8fNsV7A26/bNqpv1NBcoc2u8S47NTZ9tr/hQbQpL043aIMMLjgSWncjP965WtOndb1CSHuItUWPosTF+b02ScXooQ707iFml2ZxjlMZgIZS0aJkf4ISy67AP8/O7dhq6XYGcCuUpxRrun6nhr+0KLtqssAWh3eKP3Q/oXkBzCpFD8ril3ugf+3rWfZ+vc8dvx9bAQXnphKxhbz73Usc3coh4K8QtkHK5fpBosDlqOc8Hi2D7gji8ZzMqHEkEtQQWKdkXSwKUXhV22NQk2IAI5yI6jTSeS2mAiKu5IEfPk7+gUsMvm/h3XGOKggicXKwaueKDoc4Rx266r+vHemtBHb6w1cFs2z5piXSRpZrH7cbPN/8R9/U8hUfmpPDOohS7L/x0KhV3YfwQSpGPNSufHFaXBx/veAu3ujfzVV0aoXTk4UNpCnkLRZImHSKU+v/U2WJZeCf7m0iIgE9LIprj0FqLcuhkZLU2lN9hM4mLgoEPIrkVBoZ4FG2uQrZqWxTQUOlUuUIZbmUrurDLl7O/KoX10hRK9uEGto9Z1NVyNYIO0ZVC03BN2YmYo/TjczYWM/RImdqPDl1ZoV65hGyGvVaFcksUmA3qyaxlDXn3JBU81qngU5Uafj5Vxd9mpxA6VGWhnTTon/OkVBObBM7b6EBQ0fDrqmOz9g1fXubHiyXzsXo7/84XVpUAX7gJmDjbltyK5HjC5qiC53uAL1dnnySm+3gR0j2TT2Med0ZuoQ1S3iBWqG3s709tduDwQg2HBkxdf0yVgyLkTT3RqfsdqYKnl+oFCWEbQun2YWHfLqylU7G90VAoyf7ITiEhkkMLim6vvg/q2DDvMOxeeAr/1/KaUupMYunYJFqIMkJmHovXj8pEn6Eg7ogpuLPZMVA0E08vzCnTTf3bLCFGIpR0PhUn+9NC3rU5ilVaRH9rfXsywCbYhbyJ7DIroHATI5QV4VbbPt7p+wdqmJdjEOV+fjwGy6Ek0IKacua258hbFK4Ik6Id/Jjqxy4XWvTrcb2zFM5IX84wIh0DcvI5tns9yweNZmu7aPaidAbw6fgmNDoK8HRf7pBjlzowydQPFvL2VqQRyt3e8qwpHvRdk+evUG6YQkmWRuSaYYMW1YMaUqlNCmWnUIaP+DBAiiDZ6XQ2oy0cYYWPRo9mHdQrvttGkaW0B+oXr/jSb2gUhhcKsBmNVAhlCb9O0BdQm4qmoH/KAjif/hP7LD3lk3P6UFKjgjf6gC9sVfB6iH93dvnOotvc6wtT6F39bdQnHsPRtYVZ3TDIFeGkYg331B6H2Y5+nOvp5PcSc2cY8/jdvNBJVLTf0azgpBIeircDke31ZC2tn2+CUNrNS2nwB3Fmx7toSznYYulwjc+duTDRrWJV4dSshNIQX1j0ikfGnum2EHM95G0GiQpkVnJXs4IuuJnbg2XPuH1KEjdMSifW5C7yI8tjhFolhnp3MSf9JAKVVLF7IN1DMgiivwBHhrbgqw1PYabaw+4HlK727R38eFo7+B3QhFLkY5EVyKDw8DwwAt1I00PervxC3vrKUdiooHk76wwhbtYn+AbIn9kGiCmUyH41k0JpbpBA+XbMdoPUSSKVFnQNhVAmomjxFLPVDZ0shU4NvkAQ1f3taBGTWg5CyS4SOlZEqG16PTOF0kwoU/3oMFVIro448OfgQbh2UqbFDPPxS/ShQ7++mnWz4myrP0EoQ/pXRXlCFJKjSdgu/4MUTfJf+2G9gmt2KcyQ+4hCTqLYOWDjD3YCWplt0sOdCsrfduAG9+Ksk2uhz4uuhIZdbR0sn+mgV+7n4dBjzsnYtkgnNubqYaqUPqpoIGxjxUx9Itq06DQ8G3LhWP0GaYd4eS1WhLZha9yJx2nOVoEpbv1A0cRi8jYTIe9Zfl5QQOMwPqNYNAQH5FDV48XC/nrm/4n2Bn6sC0rQEOPk35rjVOFSmaE+WyFTaKxuFjB7maEcWZUPUlXbLVW1pL4TZlDI2HR+UpcRWrRYQ9KkKJJXJDPXNnlRCkJpzdFr0MnUxEhbWsi7lgy/E9n7WzPfR6FQCkKZZXtGuPvJC64Q5dRHO0c/bLb/mIoaRoiLUa4ThcFyKAnHFGlGtCLrvhNcLamLdWJ2fxNak45BrX1adDL7QelM+Jq35tyWrm4KwZKx94Z85qVYhKlmpKLfHliac+xWG6fcIe8welwB9KoOdq3T54xS6pBdUQ7NOdEUAlrSCAdTTl6HqyC7Qqk6Wf6pCAWKkDd5e7KFFhFdUt86m9EaSbDCKsUU3iXT9KAaTyPIAi2xFOvEUxoYmJxozqT0KavrQDaFskQsoCbMhbO/F441LwHb16G7ZjZzlrCLztCRpTzkx1lHHW7KT/OCba9wtwdzkl2sacHvtcnYEKzDf9bcihNjA84SZpxTrrJ0jmumfxJPh1z48WQVC+pXZliZCSwOphcgiZamiwL2KiXNnRTuFqB5geY+u1ScNPgLGKF8vNeNd91VOCzRknv7YDEmJXvxjr/OprsSkCgoReKK3/A2sHq4O5QC/tetYLJ5jqT7qeXcuqCCijV5CkqT5kGtJe1hlifFUp+oLkNEnej8ozSoU22KluoQwS6nfo+mQih9QcNSxCzfqRYoZgtMSj85bs6VOGuDE5duc+BvHfyYZmncdKASyiEolB4f5hqEcg9C3qZe3kbIm6qzmELpZ6vAk4pVbPbwlZro4arphDLXit3aKYcUyn7iAlRM0af7IZpAN6U3Q8DTPXl8XbEoWrwlaeGOKp+Tdc1oFYvwnISSVlT6hjbh0KhVoUz1o93cZ7ezGffXHMNUqdkWSzZSm8oYodRv+nE++WTzdCzQUwFEAjytTAnz29bz79KSWE1V3qRm0iR5e6MDNSsdmPlBAbt4JpgriQhuD8tzO1rpwFP6cSWS0t3SjD6Hx7aYpNCRQihGx0bB+xHwPMot7wFFFYMqlIR/dirseyZ/SjvQqrxXcaPFV44XPBPZeZ5tooyXTcDBPVuxspcfw11UUS0IJanc+qKHCo/YsYr1s++D2gRujpiuJ9qW0juoAlKHx+VCXbKXdVEyir8q6tgESOTcugAgEtfiL+MG5fVbuEfo1IOYUiQqb9O2T0WYsbUZRE7IlmoG9bc2nW/C1sUut5DdYIlQmkPeTpVV1CZIFbEolGwsoYb0kHe8O6tC2RpN8hxHfftyLZqT9DVSSkCMd+Ko6O8YVHEkQsnaEFZPQUUizAig+XyxQlSeH144OImja4bCyhTyntnXgB2D5DgSWmmlS4Syaj4CO3huZC6IyuP8IicRdLoL0OIM4h6HPbmw+mIS+jQHI4xZ8zlpEa4o2Kl62bmyW1dZs9lkNYf5oqDGy48HuWfQuLIRyqaEg5EDcc5TUQ6FvFWRP/3wL/m9pW03C2GTk0Zp0cD5Swt6gh1BJAJKqA560+Y8ilKIvPm0sdhECMQCqqOgBq7eDj5TblyJ7qpp7HGrF2X/pLmY9rlvI+gcUAVpvqTrz7rwYyN3e3CE2sYI5w27gTNnXY53lVL8qPHftsfrE2UqnnTUojMSx2WbVTYfv7bzLhxPsqtN7j55BpPAsNvJ8/pIEKA50i61hkZEhPL9/vSFDaU5DRbynllVjnn9jfh3awKvO6tweNy+qFXAP3Uua2KwupfqIZSMwpwk+d/SvFo7zSiMWtnH/WgpfUBUXpNCac7Ppfmc2tL+pZ0fi6aUG7VJapk78EWdUhAzop6U5kc4vggsZcoa7WH7VMOoV3QBobvNyFelFLGM4xIsYnPsLiWIpMlRQ1jUjitCKQ7ODO8Ac8+tUPJWheSrxi56o5e3Iw/bIJuQNxFKurnMXs6IG4We/lcwh9mYGyTL4YRXTSBikzMjQKtzc39QlkNJO3niD8Dzf7e9ORy5zom3+vL4uhJRtFKISC+KEO29SAmhGxh/w1whb8qZyUEomUKpk2fFwYye0/oPdzRhZQ1X+Q6x5LoW+Mh0XUVHjF9gaizCulrkCnkLdVKEvMl8eX77etvPQZO3eSIm8/T4SZ9Gk7cUE6w9dl1uHNWzEUFFZZ0uDHS3YJevApNstP9CNc6UEAKtkqkim1VVF5VlTJZFDpURBOHdaRDWFI0TWQnlZifv0/5y9TL2WFaV0l+ApX07WLGKqDI2CCXdTIWCqyuVZPQ8268xkkjqFXF6Mo1mtw0ilaaORaJoh5EhmqDoZls+IWt4qczvQZuvlBPKhs18hexyIxqNokXxpXXLIQWGCGVmla/CVLfpRChN32uZXjVrVzTTHNdQQ+0FTfmipU4VbaSWWmyS6IZJN8W6vuaBdAm3DzWJ3qy5hS39CWa35fTzY1ieirCbbzbSR+/BvDGJUEa7BiWIFPJkVd7UmzvRiy5GsnMX5RBIeVqfB4ljhUikUIYbsGMQWx/C+qiDeTq+UTAdgV36NZYDomo8X4Xypsln4/ypn0UknhicUOp+nA1KEM5ICIpNbjmDniK0C/wc2K3yky2botkc4tvXlvBzrJI663iKB/xobVRncc6TSkSG+pSyo02ex9X4nR8Ad14FvP+68f1UFfjSchzNudRpY+nnOzfbGAnrM7vzho43zR3m4hm6Vin9obu4Fq6w3oln+zr0uvg5bs2jTBRVYqnKFz2rnOXA53/EUnZIzbKSD7LJIlHlcHSy9JdQw05Ef3UFngl7MYkWTjaFLVT090rxHKBpO5uTjljnQEPCgXN61xnky4zFARXvuSuBL9+i+xdzxdRabCfC+9T9x6xQGpGBoMe+a5aOM0tSiMLJQtKvoRzTkt0Z6QNmTKrl1ew7wwm06zUJti1hmUKpMQePN0MKW7ATjDnPUpRDBUu0bqN+62zsKSez9DJHlE4uiOFp1nKTV/wTPqanP9E4zKozCRfFWhz1EISylYW8jevf+p0Gi1nhIGtZSqKDzomEZ3Y+dnUHDKEk1YhOfCpCyNbSTaDI62bqAyXKU9IyI5TiAqCVxRB6eRu9kLet4X2Hp85nNyzKs9viKmEnqpFD6XTCn4ojkjOHMj1ETrl7TKEUli/DQZwrlITHuvgYqpwqqpJ9/MZJZGOwkLcglPSbCoXSQt6kqOr/uHkIO63qsbMZPe5CrI+7mH2PGcV6V5COiD67RsLM5y1byDvo4CtcgaQniI2BWszr5TmM1rA3hbzTJuI5K1jiPLWRm2Bpnk6TJZmwd6vO9AT4UBd2eyswSdgTmVCkxgx7EVolzw8Ac/p28/OpoDSDDHNVIv19SXENOnIQSg9X9dqnLmWT+LFZOmnNcUYQ0BJYqXs/7kgjlAMK5UABWQSzfMCmKLc8ocnGyBON9KUplMK/joVrSb3spLzA7ISywgW0UA4Phcd1jzU072QGvrtcJWn5qKSY0KLCrrCFKqVnhhvSFjAVSg5CSTll0c60fNEyp8ZuAFbrLaHCpIW83V7UJENZFcq2OLcwqfR7mBLC1HgWqrffnt3YyOxb01AV70YXuy5yFOVQyFiNwl9Rg/JYd87wOIHObeF7vj46OImrj2rsxj8r1paXQtkcSWLG4b/CztYO1sZzMJAiy8aSJ6F8vWIhXqpcDCWbJ6oJXfqis95TCjedf9lA83g8il0O/p3u1gbOdzs09/BFcnUBnzto7mmm+TJLDmUj2VrohuJCNaNiKqZQ7tRJd18Xu07EOVqln7OEQrpZ0X3epnVkSyhitLu0pspYbazY++rH21C/9JA3nTdqcTlc1BuaEO5l6QV2CqXm9mBZaDu2eSvR/bFvA9WTgXmHYhfNHxYSJ3IEj3D24DU9z5Idk4TC0o5clg4vJPIQge2gNpSUHqZHtDb2JTGxv5XZGVlBhGlV5UH8mp93aM5c7dleflCo6NKMerIEq6kBThpwmEiDouBMtRHPoYLZL72hcXEhl43bJL2/8O6Yxu6nVZbxGC1hK+pY6hB9J2/0KYbVkzDat+ZQnl2mMcuzXv0+Qt8ppd2IOWyyR8NBviTub3ewnOwl1GGtbgY+UuvDO7qibLaOEmkKu/VCV9bOkQQOp4txJRpXmvgWLMaM/mZsE/OBTmSJk4y7HEq6MYkewUIKzoY5Otd4KuQZUCiHVJQzEPJmPpSi484jv2JhjtKX/8YOfqMSQERxpSmUfjXOwtrZQIUtZmmZK5R5TMr5IBZFq4ffkP/T5WCrV6pSrNb0PDRGHnITyrQ2Z8z4uti+KId8+axmzHql2VtaCbOzMKNYnzg7Ivr+o2HWuad68jTg2I9njIUUxzR/uMJS5o/HQs0ES2GOCHkbOP4TwOZ30UgKpdXry+1hnUnamZ2HhVD6yjDJ3F+SXSgaqw4U+/9bu8IU05dKNuJg6g5kSVKnsaeNZeFRwPKTOaHMoVBu8VZyIl89FS/0uXFcFvujJVoXC8W8qws326MKJjNCqfGbKS2GXB5o+oThjIVZv2MR7mZVz2KSJPXHdCxL9RuiEdptawBqpjIFhgiNNQxf7kig1aMnhdMKmapBP3gd6OnAbl95WvqA0ZnE5ga7ldoXUg6lyTqoQq+wFeqPbcjbdGOjKm+qxLczcqccUFLsxPlf4ubpKVlzKEXhj4+OpZula3Sa0ztsCBY1NSBvy6mxTtQnck+vVPTD9o8oC5FzApoLlDfK/1pvUwVsRUNMw5K+HSjS4tg+WBU2QVcBHVtWDb6tHoIl1XdjHuTWyGmk8ywfQqm3KdwdrIYnF6EUld4uPkftdujncZYcylAkyip3a7wKm3dJ8WumiI6lElegI55kUZG6gMsQMajVI1OBBKHUIQhlpamKvMjNj3t3PPN+0xePo9/hYREka6qMtbc8Ff406U0pzK4YJcKaqrAMLiK2BI1yyYXvZ2YEamnPFqwK1HFFjxTWyXPZfGAtRFRpjoyHMNcZZY0NBBojKTYf1piU2LSFaKAcaNphPM5y+fqaMghlsUNlYfZVFQcxj1AsO8HkJpE579H8RkoapfeYwQgoomnChxml1RNwVO9mPK4LLE1JF9pcBZiTw36QR2+A+kiKzW3VJtLPjo1QFMtrDbugt/rACl8p19nwojQRSorOkHsHVeQPjF3jeeBefiyPKeLz4lPdDuZdTCb3px6ynOWR/yrGVVOz6ihy/euT+klBESXiLcUV7DiyFCXT9lqgENOjrdgWF/UU/HqhaApxBYvuwnBUYPDuO/sdoSSZl5g5ndh0Ug1WmDPHy7+Yx7q4TFxOuUpGyNuZ1XfM3ticbFdMK/ZN72DC9nfYn+RrFk0jlC5GKCncmg2sl7elytscGh0WElG8VDwPd3f58XqfwsyPa9U+VCHOb5BEKE3hTdsqb/NqvXErD/HrpMtclFPodbOk8rScMjJDjoTxlncCs1Ewh/ZL9NV6R1g/ltEwmn1lqKEb9tITMsLGpPKlKY6FZazH8HyEbCu900LelB9CyfLvv45GZwFqTS30GFxulCT70WO9iYc6mUI52UJARZgppOd2UU7fcRTOiWm4cfuDQDFXFtPJrT4WqnA87bPAomPY91xgQygDispWk5v91XySdzjwom8yI4FicjNjuhbCDmcRW3ETKLxEn5+qVo0bNhEtnWxNUftYbg8plARSJAyiZ1lklDj4ZzcUs+1rWbhKC5boXpTpY6EbKCNxYiFyzzXAm/8FetqxO1ibFkor17tOtNsSSmBqvBNOfcyq04XKVD8zbBYdRzO6wVCBlkhJ0XPKKIRpR1oYiU4M5FzW6v6CQvmxQvTzrnYrA4snS+6ndTyECbEu1gFnsO4xgrBSOkpNpCOnUbkAEWua+MX3mAv0ect04/Z8Qt5oqwfWvQrHhrcG3xZgljNf2a7knOsMmOfPHHZEAr2RKFfSi+rg6RqEUMYi2OXmURmhVLLIih3iMWZuTl6UIjLSSu1oE/aEUovHWMOJCT4na+tI2FauNw2gtoLmMZNYCgeq9FxbQoFQKG0IJVsguIKoNDVhECHvtJxL6rx0ztfQsfBE/q8r3cOY5SO73HAKQklqtn59ZfTzJkIZ3oVVW3cCf74ZWP0SqwsghYsTSi1NXDi8dxP7O02h1CNMEwLuDIJIoC5HQqEksGgIXXfUvcs0z4iIyiZHMfDU/bwZw9HnoGnackywkcoonYXfa9LPt4YU5Xz3ZO2JfdqkEhYV+c8OHuqneaqJDO5zWAFNciSY8Xyc0nbcRCgV+5B3SSUOK3Jgm+pDayXvo00qpZGParINomIdWsCYQ/ZNVCSmxlHs43MYjYmM80OqwpwvlhQ5cW3fG3i9aCaeKF+WoVDTvYGEhUZx36MFvT4u0a7YXGBaEfCiUI1hG4UaCUaoXWF5lHYK5QkF8QOPUBKZpGRluhGSMjRzEIVyrifBWvut1BnJPMrNSuvlnX/IW/N4M3JyhCTfCB8iijs95E2EMmdRDljHj7Qq7+GZ5WeEvC/rrGbEtS3lxNxwIyPkTBGhKvJ8Q96Ed57h3REozG8pyhEdcTL6D3c24a2imSw1YakpKi1Wyx1ict29ES39MVR37+YrJUuOjTWHklbUHwTqUOFUud+biVCSrB80E9AJ+r6atqERfkywtjhzeZji1GOtvqTwmbOQ9dg155NYCSWBVADKyZne35ypUOoV52zyO+1zPD/IX6CHvDMJ4hSP7uUYmAC07mZkbFXlAvbYfJtzvUKLoRUDRErk7kyjhZYI99FkoU+ysxV+E99kq1CmmzFTZw/VfFOjwiMa8syljDSZJzRSeQqQQgvlLQqwFTnll7ajw1fCjMwFyv38xV2xlK1C6YZqeI2qngAqEyG0MVXQ3vuRVONCXQUShLLdW2xLWihJvS6le6vS5K0bnWe3DeK/2Q2fORSEmBl5Nhj5dvEuTNPCgxJKkbtJKuvieAs25/CVFCD1g4h3rgiItRCJVMRd+RBKWhA8/jsotMDIA5RmcXdLnrcQk2KYtWuTCVokjD/UHosnyxbBI7wMsyHWj62k7BPZc5eyuTqr5VEizlwwqp2qQShaKKKTRaGk+YBysGu9ClMo6fiHfcX8HM/I61TQCg83w9dR6OIpJqEseaMdjoBRWGMOeactpE+6gN27OotqjMr0NJKle7oaIW8it3F+DRVbOoZNcsRQrMawqqWHdQbDLvJpBnYVTWL3MKqdMd8LjuzZhIakM61rT4Ne2GQtdBQKZQcVG5nOIcrlr1QS8FIhrMk+iNwhCE27tgOb3mVzHo44Cw2VM/X7a/rYKV/UrsiN0iKKUlEUuuzPxTODEaz01qIxmhzwavaU2LaxZPAX4oi+rVif9LLP0eYpQpVV6aW5VY9iHlrqwVtVi4ETz2fP0bEyvCipva+uUFI3McIa09TU1J9MO5bkIsBydEsq8V71IlQ4Uji4bzu+5z0YXZMWsBQ+c4SICGWjuxipuH6xhzp5JLWkyrj+zQLAdDd/vx3hTD9nyu6wK8qpGUInn/2GUIrV4S69SjVrqygdc5xRbPTVYHOE9/2dFyNC6R5aL28j5K3nUJogTsYmzY2owzXwRVDIO5VgxCsbiOiRWiQmvRFVKMXKXF9BUQX2wjC3eMgr5E2tJZOm2aN+E+9xvfzkjKKcchHCtqpNnc1YWzmfnfzmwpxSl8oqqI2bYWczmte8jRpa0UfCwFROoMyEkiWXn30pcMWvgYNPxge0miU/sq6taRcDJWsTDFWQbCqoMrS7DY2al4VO0xKOXW4WmjS2N6Fe5VfgRFMIKOjin7U3mX7eUJ7L5FgnHFT1ZwKFrshaCIeeDkyZB2xexQllFoWSqpMJLKyltzqrr5nHimfIn9KKCi2CNpP1jmj9xyYyccP2+Y2Q9yxnlH0fYpKhSZ4mGnYORtNVa7LHoVZxRns5OmdIjZm9TE/0HhgPVb0SWvWbWhp6OphawW+A/DVlekeYDr0gwc46aKaj3+RB2YPWLMqdIIK1IncUGjuOrWRXZENaaOwTqb+1/llrwLfJFvKm87RH8aCa1G23B2XJvpy+kmI/0yKtmOiIDUriSG0hB4IjejYxs/fVpl7M2fBMj4KHdYuPwSCskihEOJhNz6jD/H3kEfKmc+6SOV/Ca8Vz4Kb2fYPse2VgMo5e68B7nho4slkMMWhochWhxpk0Ci2IYCpZciiJULIcbDdvOrA7rugRK3tS3Kp5mKouUORS0OPyQxM3fAs6HV6Um9o1kkJJi07hs8jCxDMWszSSVFEFK+6hat+0HEonn+uNkDddO9F+du5avSgXqV3pfcKJgHS1oL6Ke+maK70p5E3We7xH+MD50xGOIKa4MMHSt1xYGHV2cIcDAQq9EshxwOzMUVYQYHNM25b1/H77wE3AnVeiYetm+JFCMJh+n6Lwvl2ecWOQm6YbnbBMcDgcODVZj/8kTREkUii9Zai16btOmFRWjJO61uGBbh9Py/IUo8rUXYmQ8vqhtNXDrSax1BvHmyWzuR9xWS1rOTvFJuR9kF7RLhaebOw6Oa/VVRo6J6kmIXn8+Vh91GfYY09GgnipJcz2by20oXtUvY98V/VzjiJ3RMxLqlgeLtVmmCNc05382tjWpw/CJCRkUyjNnaUOHEKpHxSScckkmgoMcoFMVTd4K1llLSmac+NtTD0cIJRDCHl7MicQStCm1Wo8pSHi8JgUShd8TKHMvmsxuQsSyjvljNCEL4ivx2sYPItqd6a4hLp45xOTKas1x0axWK7g3WeAWUugFZbx1ouGQsnH3CmqxwU6m5Esn8jah5Hha1q+D3WlsKpMTqBg5xpgmpVQquieeTD3NaRiqLIa1sucBNH5vTvSCaU+cRrJ7EQom7axP5t0KxGzskar75Jk2Lb6klRwEaIQCOoFRSGLskaThwcpTLDkE1H4uSdYzvM4X/0XsOFN9p2EVQcKHDk661C1NBHKlp1I1UxjyiOFva2oSobRKixS9BaPpJhO95pD3pRzEGCKzSyvyhZiVFxCoBsjLWpY2I/IvJ5LQ6Mo1aLogoXcbH6XqdQNSbqRDDws7DRaRVK4GT3trCcznSZBk6rd5/AiFsuc/GmxSF1vpyNsqABkFN2eRUE0FD79hkzvQRNim68EiGVWBVMuV7GSRCEppgqlgkQQgstIG7ADValT6z1NhLxztC9kEYGkgsPbefeswRRK+i5IZT6jg+csrosO3g7utkYHrt2d37QtFg9b8slxHG3EhqZQGjZBXa1wZCN75n37AizFhxT53IQSaHYVoMYRZ+cuiQ0dlK6RpcqbCGUDKZRulRVa0ELMKNK0AanplVSYpV9nLA2HFsVZjNk74UGZqYiHFEq2/dxD+APUm7tpO7D2FRahoUWIWUUk1a7dU8iEBIeZqEf60OPwGQttgTr0o09xo9V8Hu9cj12TuDOHOT2FznnK7xPFeAaSCTR6SlBnyXOk+Z3Q1dFmex4yQmlKT6nwOFjLwFSvHoqmotRQJxo3f8D+Dc7hY0pTY22uv4Zi7gXJetdb0qZmHXE8SlIRvLK7feBBplAWZ3UX+UxFkuW2PtREjv39aHEXodSRSuv4xRTK3g4sblnL8qbfjPn4wnvR0ezzGqTPFPKmLj+8oMgU8tbvJ6LinPmckgNGoBC7N23Aj+sVfJ0cyndvYPePJmodagl57/ZVpHeGorB3GZFshUeiTFPzdDWMNsWLviidyKl0hVK1z6E8MBVKDydwNPmTKkT5HtmayFP4cxbC2OTiqtHGCDA30c7InrYnVd7uzJA3fanMNiMRR8zhHghhO5zwqaRQZt+1UVGlv2Z0FEp+4bbBa1R5MUL57nNcoTzk1Ow+lFZCufEddgPWaqcx5VUQygo9lClsgNJO6EAhtiYokd2kUCpJdDp8toUJNbtW8Q4rpgmHVL6QvwR45Z/A/+5jq9fkP+9k1c/LQ9ttK5M7zvkm8/XjhJLn8TToFjVplYN6kUWvKYQtUB9NpanihKBbVygtuVbUJcQINVtC3p1TFvFQzksPA/08BEQKrV5AaG/i7i/m3yGFo/wF2Jb0ZOyb/qtM9bHWgGYQgZlmVii9fmYTQYbHM6iC3HQKC0sp7kVJRTmie4yXKbdWn0hGKF0eNBbUph1HofK0WjrTMPT3okvxphXj0CKkw11gW+lLuUA7lALMVHsHCGWil1Vb57KtqdGLIKjanNDuLrL1c01TSvxBZijcYkobsEOb5kEVJfy7fTzkPcg6tDGm4cimlXkRSkIzPJgbacL2uNPW/Ho4aNLzLfcNQtk/ZIWSoJBzQD77FrlgviAc8dz7p/SMGsQYoaDOKSpFonIolE2kUDqT7B60ixRKjz8rKaYUI9Z4gSI9+rzEKq6zkNwOzW0Y5guFsptC6oedwSNq0xcCG9/mQkCwmIV803MoVXRQlXpI96AUiPSx97XmUJZrMbQplhya+k1oq53HFCrznKe5vCwfuEncsExochehVrTB1UGfNUwRKFqg2hLKDkPoIFS4NTR7aPGX/n019PHjUTJhUtrjRJ5tFcoynt7EPGDNLWdrpmHpLO55+l6DnltISMRZXiz3P07/bBSx+Yy/Ew9WHIy+cJjNpa00n1jMzdk5EA3j5Ja3mFr73qYtLP+Yii/JXJ9EEhbJMymUCwJqRktNup9SL3mDUOo+pxrdo6NhtngkAY25ZsRjrA1pWsjbq3BCaT4fG7YCs5YBn7keDaonTdGcluzEThTwc8VSjMlS8SxTEJFoatl7wBFKxsT1E5MMZKnNkfnCMoOqmjxQsUNP0CbFaWIyxImkHsa2I5TlLo2V7Wf28qYVqTWHUuNJ+Mk4oo6BHEpSP3lRTn4KJeU2koJjV3SwRxDj1Lv7iFAkJc6zfEQie5QXediZafYsaTmU1smVCm2iYWil1SzkbSiULiDk9CFmDeeQ5K57yJlXR2VIoN3Scs9QmZo38u9HGAaLkDeFc8RnItWir5u1ijoksjNNrhcTZ09RFXDWJbziT1coG2MD35kBlydryDvW18v6oZuTmYN6cn3IQp4N3zFnOtGk5OteyuWjmwFNWvoNkiZcu5A3I89k4k7nJ1m20ARCYWBXCVcdzXC5UBUPGRW/AkRgWMjbUKn97CZEPn7s+jG13hPXElMkaGw00dPx9/qZ92JGgQhVD/Z1o7GghpFDkfZAPn506rZbyK3V/kVcq+VuBe2sCtv+hrxb82Ei5TnqYaUK+pw2+ZYEOl7UkapKJ5S0uicwlwNTPlnGZ6YbT/VUZhlkJeVWtKguVKsRuCtrUZiKoiOUO7+Q5oTpFNBQqfPM4NNri97TWvQmH0lQ2JTC40927wPTvLlIJh9CqbtqKO31g2/LOkPpRv6+AByDKKBNip+lwNDCyFD5k1lWCvEIc4kod6RYO1u6l1AnqWwKJdlhlSbCRmiXWZkRocymUKouRvLSIhtktE4L4qXH8QU2pcsQoWSKptvIoSRBhQhoh78MilD5zB2E3MGMKu9KSpXRF3kGutuYp/DupDMtKkNkiPJ7G/UFthkNzgLUOdLnvCKPg5vEW3Jw6d5Dod6J0XbjvsTG4kwxpdCa7ywWirWIpNE9YZFkRaxiEvMzrosP2O8Q1BWnYGn7B0yAMnde4iHvEhbRsHoCU9OAaUoEfwws1B/R0KLfs8z2drTYPT68Bdd1v4x7a45FfMM7wLrXWEex9qIJRt934UNJ6VbU/cZqecQ+r6sItfqxpPmU2fAR0TN3zSO+0rAZTcWTTAt6jbWHpFqRtAXOq/8EHvwZi+jVF9Sm2UHNiHVgh+7ZynPn0xVKilqZMWhLSwv2gZkmP9DKSagqwkKEfWE2EH5hlDtHoNdNUnVCKQpzbAjlLVM0vLNY5Z116HmRQ8lCHJkKJfNhSyYQcXoHqpn1opzcCiU/uWk1IEKBIxbyJiJMCqNuQ9Cqr0Z5WzX9PV59bCCcYqtQ2kx+Xa2MUNLkQIRS0fPVGDmwKppEPui4u4vZdyGU5DLEWIjHLu+sOtLJiWyxaFum6TmUJkKpg7oGzUt0oEQPQxPExMnUAL0dllAoe6Ix9Dvcad0XPC4Ha4km7DXSEOrCLl9lmo1GUE/4Dul2JgJ0PJpVF6YlOtMIunEjERe6IJROn23Iu9CpGqbp7PNSPlS4F9uDNYygmFfSRX4/fFoCrRblgAgly7ekPBq9/SIplK7+Xv18Hdi2U8+vYYqEKC6gycVD3YzC6ROwQFcr6gv5ZClWvbSi7nT4kbKeA+J9dIsoQSipAIHddLIoNpS/WkeLP0Oh7EG73sElE7wIgiyxCGQ6TWhz2xNK8fmZddDU+aiNdaM9C1kVIFJYlQyhrIZ/7i5reocF1E1ILDREekHO/Xd1jxqhJFyw2YEn8+mwNerQz0lKNcpyrmTgiXvhfO+FIRFKOucdWcieAKnSDr1IolXVT5psCiVTs4qN+ZrlUOqtTO1A1xXl2goljiqfecjbfv8dqoP5m5p9K4WHJI79BLfgIpWWch1p/4rPCHnTwo4KVTuClVD059NC3u4CI3IjQPYzbZY5WOy7nhZzpjmP5neKbtkplGSXV0vKvQnFbidLcbESSrZvCr1SW1JTBIoKdciH2Hq/oTS1FtWNOrLTMaVm2RflkLJUgwbFz69rk8ig+QuxtGcb3gvbFWaVZHg6iramvYoHryUH8jfFotNMKKnhwj+iz+O5PjeuXNPF59B2rqa3BisG8stZp5wEZnqSTARj7Wytx9JZgIlKjB1r+m7baZFJc7H1OK5+kRcssbi0xvbPzknqSGY+52n+p0LK7jY0uItRZ8rnJMugXbr5P1coB44XBYIsbnm2DiO5sC/MNHmBvnhhpGsYyGYhlCI3okmfLEiZKNISKMJAtxw72yCyIqKL9N/zVKZKpIW8LRMIjadZKJROUw4lK8qJI0KxpiwQ90f68gShHLGQN3sDHqIjtDr4RJuWM0MnErXU03t+Zu2UY0ZXM7TSKqOlJJ3IFc4UN5G2knPqAZ6Mo95XwSq9xYVYqkYzbFeompHu0dV04tL76it7Oi40WfZQzqWFfJBCSVihDUyiRfrE2eOkFf273OBVmMRHwjyx3jSPMnsdCmHbhRlDXaxSvlq3uCEEnArzr7MjTmQaPZUMs/VKbyLQzNicbgxi9a1PDn0uv60PJbNIEmMRE2zrTmwtmcoUTfNkVhnQ82MtZKgx4WCkmRXasLwyrlAWhztY72JqUTYAvV0jUygHCKVG7TGTIXQmbM7f7lbsKpmSlrxPqmCrq5B14rFDVyicRvjLnClW2ZqtCrcx6WCdI0jp93i9rHrTzoNSoFX1oJKuVRby1i2dSJW36axCNyoq5GEK5ZT5qIl1DEooqV1pdaIXZTV1g/baNlsHUQV0PqB+4QRhWnxAg87JWCQPmq1j3auZRGkwQukLwjmIAtqs8YlgYQBo0VM1snXKITQqwbQ8XyrKyRby7kxqTOEXIe8iJYkuluajZSWg5FQgCgYLnQq33elo4qSUiAFBVyg7XAGU6XOBWKS1F9ZCofxDa8jbU2BYtQlUpPpZGkcaQnxRU+8IphGIKj13zrwQNY4JfKijnEUTit2KrlCG7QmlJeRNkQVqxWkHunfzELbXCL2SO0aGQkkm3m4vdscdmBptS+s4Q+R1abLVaDFpgNkGcUJpzaM8slDD64EpUE2KrygKJPVQYFG8FcVI4mubk0huWT2wKOkPoS1YNcBP9JD3HG+SuS2Y20YKbHMUYgb6mEBG9zymIFN01HocN7zFUmroXkHzuRA86r3l9udjfwj13jJD1PF7vGxu3Zn02Lp72FV5D9ojfX8llBSOFvlLhoFsltZJFNqk6sk2PeRETvqESVrYKMyxq/ImM9L7WhXG/C9U6vm3a+6UY0Bj5ITdoJlC6UszNh80h1IvAqAvT5CLEbMNItBY9ZVgi7PAaFOXBtEy0NbY3I5QtkIrqTaq18mLssyRQocraHODoEqzDtQXcIsIceKzHs4ZFbt0k9fNeok46hMIXTCEkI1CSbmApHQekmxNC3mH4UKKij0e+y3w11sGXhDpQyNV9ZlsLgTBoWKWDIS6WN5MlenqIlJH4X07ZW1HJIVpNJnpXpRi7GkKJd3k1BT63AFGlq2EilWFa8708GDzTmyr5nZN5sKcKt16p03vBSzQnHQyAs8mMj2vTCsowQTqUmHqbCJAyj3zohTki/J2PD6mUNoZj7MVb8UMNjGKMApNgsyDMovi2B3hj4swXYVNHq0ZDXEilF1QvD6U6jm6VOiSDa2qE9WkCDmcbCzd8CCh56vagZkss5D3ZEyIdRtzRDa0xFKojPcyI3lzNX02iJvvYNsJUMEDpfGS59wBD5qX8gl3DxW0T1oIU458PiFvXWiguVeEM7MW5TDyNECCuEKZvcq7M67CqyUR8OiEEkn0WEPM5u31hZsghzznMgisfIo/sOmdgc8Yj6HTXTiQPqJfUx1F1Xw+z8ihDKLYQigrk33M+SMNVDTS38vUQjPBqtaL3WwJpepmLf+sbSA7aex2CmVMQR11hDGHvLUomq35nGL/SScPYevbC1U2o8MWWdoBWBtKYnHfrrSQ92QlilItbksoyYuUwPMoOYh0Ucj71dL5RtoW3zyGTsVrLOopijct3sGu2x3Waa+3E22FNUaOqCCUMzwpJmyR8bkVm5UizEz1GDZWrfo9O+M4ahoa169hf9bVTTTuq7uyuFpQqlq9v9IQdaYX8IO4K6EfTGsOpU1RDqVE2Ubx9m9CqTGrBCrKMQxk1ewKJVMPXYVQdWJkGHxSbpZowm5R1WgFRCTx1RAPw5KNB22riTC56YZJJzflGvCQdxxRl2eAUAofyhwKZXrIWxsFhTJmEMpWUhBNSogBWoEVpZtxGyFvs22QAHnBFZay0DGBeZYpyYyqbQNkal08yVQ5qKGC+n7bkAMykGYXKylzIvdIKIjmHEoxRih4GyU4JDqQsF/i0phNBlt10X5MEwInlKWoMxFEqtpjw7RVKDuZ95h5wVJAnW9syC1hRziFKUQoyUzdlM/Zy9RV04UeCSPsDrB1iqFomwmlqKwWCmXLTmyrmMX+ZMU2OirJCJ4RyvSZXuTsseNNEwx1nPEXoI5yl2xuDER6WEcHMXHR5MIUyj5bn0hSKBNFFSzHKU2hpLBVFkKpRiPocgYGQt6IoyPHDbYhrsGjpZgKK5SYXAolC0lT0wLKt6RFpzMAJUf7Uto/tV8kQ/RCLY4dg3SQaY0mmSnyea2vY00ywAztc0GQ9nwJ5Z/aFJz8vmPkOmXty6BzMg9T8z3aL4FC0XmEvCmEKabbVoNQZg/DU/ODfjhZigiJGjkJpX7dlOkevcVIoFvJXr3fEU+3YCtypPhCdP2bwB+uNXwiGUKd6PQW6+SKh0fZPtyFUHQF00Ckj82d1qIcRijtbLh6u9DoLddDwHxM1UqMFcrZtT1tTPI3N0d9mK2PTQ7lgLl5lyEY0H2vAEm0WMPvYv8JB2tJSB7Q5gVpRoRgxalMAHinrY9VpJtFg6XJtnSLJIFEDCGnH2HNkWZuPq+mnAkNr5YvSL9/kHWQs2AgSuQLstDxbpX8PSzXbagDieIq5uFrKJSpBKZ6klmbEWzWAijQElis9+2m/H3+vpnHsZEslui4z57PFvUUMWQpPnbnfH8I2wsnsj8pf3OaftOhwjLxuaw5lOZGJEKhpFajBxSh9Os34IEKS36SZyWUVIFtuslRGIq+eJbsL3IoLSFvVjWu0IpDYSdDsZbg5FOvGjNLyqJsn4W8E3FEnH6DULodDpYLEU1lZ4iC29FqYEChHMEbClP6OKGknJaE4sycFGhFW1ieQdQyjM0FKJeHotlUhawrlBVKAh26B1oGetrQWTLR8MHyu5zwaUl02IRSicCzXD7TuEXuTzYS92YyiEP6B9p7kSpINhm2fYIjfbzbhUm+L9UtLmwVyv5e1pqrUiedYgIMOb22ubdU6U1hVJeuSggzYRbytlh59JHFhx7St1ok9QpfSfF5O5vR7/ShOeVMUygrPQqScKAzHMlQKI1Jnt5XNxEmJc6WUEZ15VNMXP4gfB4P/GoCndbKfXNubMpjrI5Jzaf0AKsLgoFoHwvhcbVRY4bsXVluImyMEd1GI+BGmf4d5VIo2/S+wnTeUA5lG93QTH58tubm0Q7M7+eLkS2D9Lhu1X3iTu5ci1dDg0+XoqCAWmHmA2ot+rKpC8kBjVFTKPXrgBZQHl+6fY4NKG2FijgIhkKWzdickIih0RHQzb0VaB4flCyV5J26eXa57rdKqVY9Oc53Y3s96lCkpNBNcyqFO8npwYxQFyvAoXsNixDp8wxTBa0pHrpCKbwhCR6ng6WQUBVyBkKdaApUsvuRWMwToSRyY/jRmkD9vDMIJQvv+23JOYk65M/p1ZsQCHLWnLK/idNcZVY0y+wUymUnco/OJ+7BKt3/bZl34HtcFmtCk+bNbFxAC3aFct89aRY8hx51LLtXvlU0I4NQUhRG9PMmb1/ymt2esBl7byfr6Eb320rdnowUymnuVFa3hS16TuORegp+GxVzEmyIObVqJNRVVWGSV0EDc6mge6eNCNQfwqbiqczLmDwwZ/jB7JDaxT3YUpQTswl50727OZ+mCPsToSRrBILZg4p9YVnEBVaBTf1WddbOWhPBh8nJ3qwK5TT9BknJ9JTXR91CGESOgemGaRT9sBzKBLMN8uvhcT81z6TvKm+FEiOvUFKVsL6yo4rE22pOxuOdSiahpG3MJufuHAnqnZxQhshbUSeU5YihI0vIgl2Qpdytn8hHeUAnuDYtyN4MKTiyEPCSd2AeCiXhrYiXdVGZWqgnvxOhdNrnztGFSfYUlabJNadCqWms+rNQSTGPUEH4QlmUNcqXo0WEcAgotgt5s3GEEPZxQmmt9GYKKCmsZoVSvzFuS3n1whyOKpfG/Ns0S5iOTLeNXtv0vtSyjchZspctkqx+i9SZhnzqKHWB51wWoExXSrqy5FASdilB47NS7muLryyrQkmTFi1qSr0uVoxE7gtdrH+6PepF5wivAxV6yE1EJuzQktCYVyUplOQr2OopgWJjGWTu5z0p3oV54Qa2Ih+0PaJOKOn7faVvcOPxNWHgrmYFr4wXkjgUbHib5YGNOASB1FNOBgt5s5CnbgXTKjo85Qh5032kyVnIco41u1a8JnTE+H6oOxRFvQJIotvq6Zq2PZ9ry/wedo4V0vYsz9zm+iOFMlhpECz6oTSZpMOVmUMX6UMnVXk7VLj0/MxKvzv79RTqRHNhbdr9jRpO0Oe2A+XysW1Ni3S6Z1IVei6T/YmOeFqoucXkpWsGRdSoG5pDX6QPEEp9AxI+TvgkdyzZtpZ9N+2uIJa6+XGgqvVFkQasTtnkaOrWb83wGiF+2v7I6C6866pEhCq2qVuZQLSf9fOmeZfBF2T5mrZRiF6K/JWxqEqlzs7IR3WKO4XNEfs5YVvczTgK5W/SPB3x6sfcJheVUs42J1xYEWvEpNJCNhc74jH7nPRICImCUmyIEqEEpntUbPNVDaS00TljKpKiVDyrbRAVXx5wCqVYZZk94MgyRdiEWEEyNrXLMl/09fBjIvX7zEIoyS+ROCCtpBih1Pv8ik4j5htmrX4RNRs5lG7jixDEMndRjjmHUhv5HEr63LqySkU211afhpXWPBKRdGzu8OLihEmxq/Im66BYP/oK+KRNK1myu6BOD1kJpb8A9QkHC8GW64UkHTYWFP/uUtj+jgtvNYiwQShp/zYEVyQ3zyvyDIS8zUUwaWPvY9XoRCLF5EqemP2KK2sHEcNJQJ/IaJ3e67BXGoR10FRXIp1QEoGjijvTOMLeIntCSUU5glCK1aZ+k9iq+ZmPpAB1bSAlzjpyUpjpnGQV2CyHkp8D5LcolDM7D02uUnJz81I958owiDeDiFoijnp3CVsk0E2Bwm7rCyblIJRh3i3H4zA6fHTlaF/Y2h9l6itVMlInmx64c7YZbImmEFRjCPp8mO7VsDVYCyWcWeEtQNc3FYet6NnMQlAZISvr/vUQZh9cWBUZ3HicxvqV7Y4h5R2NG1DF9qrnR36/gkwV6UVxg4S86fqi/swE1jKU7InM12nG9lFcW3w0biRDeboBU8FEFhW0M8ovtFL3wDzACaI9uiNxpgBSBykj9zrbuUMKZSHvCkPXHeVQGgTOSijjUSPdSfizVuhFhoZCZdl3UwkPjwrVrkaLoNFhXzQTjsbR4/Qb3XIo/7AE8azXtjBHr9MtvoRCmc1aqz2aZAS7THfyoM9Kt1TeznagGIelBjAoWOWrwzIHV/UoLWF+uB7vJ+zuT1QAGkOz4jOIbcoXZG0mX+tRgX/dlX7PoZC3r9RQKElkopD3jqjdcexg9z3yNxUuNFO1PpYix/wkbRBPxLHLW4Y5fi6UpYhzEOnLkobxTEcKJ7avxqQCL+odBVBIQLID5ZI7nHg/5sICUijdSWzzV8Eh7u90nZhyTu2MzUmcaNIjXwcMoRS9TsnLSoCqlrPaBlHI208t7KJp/nbUoJ7lRNoU5ZBCSWoaebd1JxWUUEU4QTfPNlex0g2bdcmhGx3zoRyo8vYahDK75Bgzh7z1142YD6VFodSoQt2OIIokbnMepV6ZmM3iQulqQaiwyiDtZBPfafGVNKCHDHYTkfdqKPPxL6vTYrtDeD/Cw68fCm80FEpRtd2bhUzUR3g3g9mUD6GHvLuoQMhuok8ljLw9kXdEq+nuHMUhNCEQxDlWoCQRyrL6ZpWfzIsynl5xbuXOFPImo3abkDfLoSTyTAsdEX7TSdp2BHmuow4KxbdmqY6kHD4e8tbPV1VlJs7Wghxzq0OWn0mrYV/QyFvMSH5noBm9Fbv8FSyHUnRBeq9gatYqb/rM9L0QURU3EWulvxlqjHonl7BWd0ujjVin6OGfLGjTQ4Z1fidrd7alYKKtZZDV3PykzjXYkEUxMINaZVL+3ItRH+viI7EPQpzrukI5WJW36M9NaKU5I1e4m20fwyuFM/EmuUvoik62FA/K76dFCs0zoktNdw7DejUWYddHuccxsL1NswWGvi6jnzcnlECXmH9tPrOwRBLXnSCUbTZRIhbyLhKEkr9/DS1ElSw58jG9JaGezy2KHMmU2w7CYaJGb49IkY2o4kK3XWoNEUr9cTouQqGkBbphxVXAvz/ztb7KU42levGc1+vB9Ggb3o9lmWtiETQ5goZCWeb3YnKsA2+EbbankLe/3DiOxT7yMO7H9rDNedPbadj1iXvHTL3zVzZCSWPZ4q8xeI1q9aC04NkeBbPjbVikdWN30cTsC6h+3iDi/aSfK5SuOLb5q9MJpclK0RryJucBSis84BTKUv0GnaZQshyFzG1pVUMHgap6zau2es2LiVQ1Jqq8qVG9CVN8vKk7gdIxyO6BoIkcA30CObFYw5UTNLwr1OhkHBHqlKOHRgWxjCZz5VCKkLfGlDlaGdjlqewxTLmI3AbIhlCStQ/lkZorvUWf1ayEshV9ZBxOyqDe6L45W6cRPd+uwVnIFMoKPadI+BJa9sxUyjOj2wzfsUJRtW3pTCOgxWPY5K/BbPIMZSo20OPh3QXs0K6TGLFaL0VCt/OwB5nnE0SeLoWiQlmS68mOpt0RQK2++qYbAxluJxLJTEIZKLFVKMm3MiO8T99PMoGdziKmGghrkSpHHG0iVGczcTPrD3Hu9/cyRVP4I5pBpu60SDMrlGX6uOwMhBm627CrsI4p8ieVaCzMvtPa+ssa8nYXsGtYqKy7s+RNic/M2rp5VBzctwPvqfYhN4EWvSf4Cl8ClG2yJVCTM+RNVd6EmlQ4L0JJ5+afmlXcuzN3Oz+JMYQR8q7MO+RNaRqs7aKzAEo2U/M014wBn8u097SACA/lNJIIQlXPWa3JjLFHWGi63O0w7nM9dg4LbEedvCuO7kFJOZTMMSERg2KT2y1yJcUcVqmTszabKBEplGGXj80JwpuxNtWHJr0xRgai/awYpEpPkckISVt3n+Lzea3GryNSBintINtCtE3PFazUCR8plN1mslrIj4M5X/odRwVzcql00VzDH1ufbW0R7UczGYrrn5VyDNk+em0+AOvnXcLuHcQvpulmjTvsupf0cqGm3Rk0QuSzlH5WQS2KgzMQj2BTgPvctlLRlzcAxSbcLfBCD++ART7Ku6rmwCnalFqh52CuA3cGmO2IYKu3YiA6KyK4+rltrfIW+bEiN/8AIpQq6zxjzjPMVpRDXXJIJGymC8+UB0EVWYxQ6t1vrAoldRgRifQkq1OCcfoEEsGhBRr+M0/FGyHgk5v0/egKJT/HNPjIvXRQQqnvWs+h7M8R0huuD6VGqqNtlwZNtw4aUCjZtoT/b+88oOOorj7+n63a1aoXW+7dgOktAUwLgQChBkJNgUDonRgwfBADAQIY03sJoWMIxRAIYBvTbIptsHG35W7LVm/by3znvplZ7Uo7RVaX7+8cHUmr2dGbnZk3993yv5mqvIm6SjTkKSupw3MVaaaltrbSQ6lalKTiTxfm2d4GLPEOQXMg8x3+3zoJw2Q/9lRXmBQuEgZcpmRjIhzESu8g7OJSzlMBhbyp2lGnilSrztXEr6nauN6g2rhKvfm1Sm+qwmvSZH0yUKG2c9PGLryNGfKamr3K55WqRUlheFqI1FMBUutzFQlio0Px0iUrq+UwanQ8w1taeSip4nmAI57UR2zN2rDS2UWsiCmH0pEQ3tY23lWN+kpsyh8mfjy5UMZPYbfSP1cnp4wmYyoOoHt4XJZSLOfXe2CqbHbkidAVeQwWR4xbI1aq0kkHu5QJeI1nAGAQ8k7tS7zckkEJXL7Ohv/1CnFwJiP0gKRFsJZDaRbyjoYwu3APTK+xIe5wwWbqoUyJ+Gg5ZwZGa63dIwrKks0WjNKZ1BxjMg6THko9bdTmOpHWQ4ZwkVMWRgI1FdAbS8uiWJXsckpotrkRjuh71khSiRavZDhREY3WHCTTuIWHUg15a8Zwve69LYk+1IMSyn1Kz+7t5CXWm6/VIWrasnSsaWkk5KGkRXCK8+NHKOlE+2TLGO1WPsNlerlk4QC2uXLF84C61e3ujqDG4cP6hoDusZJdQduPVJ85GQvvmupEcxHKuRQ5+7KMsbYg1kfpE9XzUIbEQljzUMapbsPAQ0mfg9YIoeKzt1A666XMG6qGZuozep0jv2UUKS16xa+iyrvl7ZrDrqb/eSipKTz9lF6UQ6s0uhhSSRbMkBgtiXerUGUqVa9q/adbr+gopKh5KCkxNl9S/05FK6L7TAhTRyREH+mTV9haWvZRlbfNKS42urc01QIjHUo6DqVEX8mda10s0WFoAlQ75SQoL1Kn7ZeYRNRJWKB6BzPqUArjpB7N2Uqo4Zc5wBIX6VLq5R6pWpTeAaJDwLHOOtw/5HigdZtGlS8agRBsODy0MdmCrMnWtod6+qquDOMcYTHpkLG1NHe4rudA67aSDHnL4ZacxQxEI2HRYzXpoZSjLTqRGSBPbZnasYVC3lRxnsmg9GerBmWKPENSc1PIDLU6V+Eg1ruU91BIN9k+TU9ug6qYtRxKsdN6xUOZIeRNrA1JIvdQhLxzClCQmysMbV2POXkoi8aIH+kz/ynWNsc4jVhEeFEKpTjGeMjgKzN94G+x+bBHQllYLA4Zr45JRoRCjAfbG0X+ohD5NQh50zZafqw1DyXTJ6BrinIoE/HMKT5p24Yxs3AP/GlzjihEtBLyThYvqA4GPWFzgiIf1EmFCtcoH9gwZCgnhPRaoV1uybnMkBaU9DhJkshTJG/ZuCwZGykXVGcsoXBYFPolPZROtS1pps9H9fRRW0oyKCm8S3mRFQmdOTLsF/sib2Cah9KgUQBVXFMYnRjgktQ+3pk9cWSER2ET7RkzeygLkmLvGmtjLhER+1VeAuOcUax3F8Mf0rkWQn5soQ4zQlJHxl4OPxb66PmRYR4LNivSPKohPNKupEvVZTrUBLliG1GVVSAKOn3xkHhGGcqTRVqFvOkaM/BQEjMblLlrS2NAP8VD9VCuyyoWaitEuT0lhSiSblC2FjbXnpV1/U2HklY/rfULq9UQXuuwt5YTsbWhKa0gYrNaTaZoIgKjbCEckas0h6fQM91EWnEFXczZUgLOREwI5dIEdWqBInp643pbeiJ/JCQ8lAQZiFrI26iXd3I1IFEHFqV9X5d5KEmoXM/L11o6yCSHki7QuMMtKonpOH/wDoVkoN+GxmpsVisHN8CLt30TdDukUNh4NXwYG61JGllkUOoaKpEwVnrLRA/UEwqUfc4pmKAb8m4Ix4RHVYjNiq49YSGCrUs4gCpHTksOpRxBk0HoiiZLKn5Jht/tnrbhnGCzUAQgD0NqyDuZjO/M0PM3HMJmV4EQEycRclpAFSZCqFY7fLSGlAdyHYAvokwmxc3bxUInU8ibWBvSPJR+oGSI8NzqhtzEIKuFdIkWLfhJVkLSujmUav/hPCmGXb2SWATY9M6pdgxq3hbpW1aoVd96kOFL1Z0TpCasgxeJRCKj3EYqlCtNh1huYncwfQgyqigMGgqYJw9p9xil+Nidhl1yWoe8qZNU8v/pQMoXhVJUtEHd6CpENGpccVljy0KRLZYMkTeFdO4P1dipkZ0iQkTRuC88IzPnjRPBZlGYkzQoHdQqV0czll4LBVBh96HMSc9DOU0EXi/kTdEPLUJE1KlV7pkQ3k+1repAlyS8fnoRJXK6UBc2zaBUPJS2dA9l64VjJIQPcyfghPwExtmDWJY9RP88hQP4MmescB6dUZjAnmjAgiy1ZW+mzmmqEDoZ2iPJ4+gkx4rOldZYgyqv2n4x2oSxjgjWGalJhINYnTQoqSgnG5KBh5J4s1rC142KQ0AXcoQFm0ULSqpTILtlPVJSpbTrQF0stfZQasL5RjnAfdSgTKTlT6a1X3Rk6pJjQ1VlSxcVQpMH0VpL3V7ciJkTEpgzIYHLB8pp7dIaVOM1LxYQYtX0ALx5cBwf1wGzG1udwEhIGAkEGVlaL8xMBWCpaKsBklLpEg+l0yWkEBK6Ie8M4ubJHMrM20uqC10L0X+fPcJ4Mm6qw4a84cIAfcC7r66xp7E64cG4cHXyPG13UJ9wPeNDxiqH4rm7aIAs9AS3ZFELKp3cppBfeAKSOZSJoKGcB93kpAdGVd5kxHnkGJoMztO2hBMD48okQOEoSrRv4y2lz0+ShIh1aj/vZBFPph7XkSCiWT5hKJKHMhmGUPvL6unDDSaJLPru367b7UIrzCGPpjuo5B0W1W5EY6Yq0OQxNIpj2KgKG/8ENZfJwEisUx8Eu3sSWO0daO6hVMP5P+SMgt3kmiFIdJj+Q7ktD/ZAo6lBQdJBq0JKAR7TT6B7jTT/rOhcatcqzXei13LMcsg7WRWrOy9Rv20XChHFaLeMNR6SaTFeQFEXlkIphjyXHY32LMSDOseg7of2f0QehNdprm+kvtEkPGs5SYOy2JbQ91Bq0kGuPOGUIdUTokLPuyqkdHJRKlLDZFF0R0WSoaD+vV0Rt6MsSkorNoxwJbA+q8TwfFGTAtI6JiglIM1TRouH1gZlyI8PivcVC+RDpFos95TpC9aHggh7cjG9RsIFpQkRXVrgaNuKWBBoSoqNU/rASNmP9XZVNDITjS3dcqjhxTBnHOuM9G4jIazLKsErgTx80WhTinJMPJRLgxKOWGpPtkLWhRbX3hwsCUjYJGUjlprq1yrk3brKm8L7lPuqp4TSp2WDWledtrRfTN+2zOMUN4W8bX369jGbEC0tcyaSfUopD4ES+e8dLqdVvWr5Y3kxPxK7HwJ7JIjxWbLI82tDJIRgiocyy6KHUjRiJ4FaexflUBIuN2TDkDd5KPOViVj1Zgr0bkLV8xNUL5v5OaOExpYuTXVozCvDrj/Z8GTRweJhb8SqeBbGhrYLg4WSpJd4yvRD3rS9XTFmDswBvgyrKy+9Fa8attByKAviQTToePkEYVV7zCUlJYzo5jKeLOn4ZJE+sdZDk2VbDyXhl+1pOZSah7KRiora5FAqElCUjkEG5Sh3y//LhFbNPSSh/K9BWpccHQ8laalRusYI6rNLBmjdhgztMVOPQZnoNiXcQupqtaPAskFJ9xqtxE09lGqYbX7OSPPwJeW7qv3q17iK4DC5xojHttkUCRim/6DlDFtYgCTTSsgzQxEcUw8lCWHblAiOmyIPIUOZIWoLWyiHRWFIOeXGmVzDtbITRYggP8sp8o0lkmjLBI0zEUcNXCKNiATxQ6RZaGBQUp5iMofSHhPFIrpjb6rD1qxikYN9TJ4sDDLdpgJyAtslj1hsU0SGVDyoGEkyiA6Q/ExZuB4lHpdwElG0wqhzUrXNgxJVD1p4KBOtPJSt+7yHg5hdvJeYp72IY6lbx0AU2yp9rF+upKiV8tJCbXHc9mARDAbRREVFLmBCrAbrbAbFgk21qMxTvJ1/3val+L44ZPSsCSJus+M8/xiUh5WQt5mH0jLkxPDm4O7NEv6Se3R6SlVqh6kMVd7kfGnTmciEPhTyTn+NdCgz9fMuy/MpkhDb1qW9LtONKJKfld8paXpek4SJS+wYscCGI5fYkpIi5AYn8t+6H7b5n2DYiq9FP8w2ivtEPCZy/zQPpUfN6TTOoVQ9lFIX5VBqF0pWtkFRjmpQki6nL79lxU4hQ50VuzbRBeGAPw4syx1uHPKmHBdfHjZEyBVbYG5QRp0YHq4RXVLIa7bEO9jQUGmOy0JflPgylmf8QCEPpStH9VDKwqCsN8iJFB5KMkBdLd7EJgNt0YqoTfTwpetL6CGSMaxjUDbDnjnkTV10MuRQUj7shrAkvAYH+mT4bS6sjujlUCrfB6n5nKLbhBAAzzxubRE1ZttSuGe+hImOJvxgpLeoTnRUfU15rwmajEjHL0OVqUZq5edqb5l+VaI2priSwzkva5gl7YPtaiVqec4Q2A0KclLzj/7TWuif6dto95qV1o4pIW9qNWueQ9ny4JVdHlMPe63sQHEiJOaB1VS9q5dCpFKTcAgD9NS8CJZSmNbo/giHlMpucR3blK49el4+krsh/UT1di6VIsLrp0ugERWeIrGAPqkggRnF+xmOvUoNh9P+i9120QLSyLNGWrj58QD2Vic8Wlzqjl1NBShBSKRJFbQJeWfwUIYDiLh9+EwtoFumRrAyQteJ24t5zSTnQ8arF5uiBuZQc73QLP19kSyq3z+2KRJLutX4+YpBec72b/Blsx1rTHIoBW6PElUkj6GJh9IydC15coTj4EvfqHTPOj27ad5W6y3IZqFFP5UPESQhl9pMph8ZlIk2BiXlHdJKJLXSm5KI9/PGscWRm+zskiQeE+LWRVkOscIsEl7PlnZsqe3PtKq8fH8VHLPfwKhVXyV7TmciqBamULg7S5LFw7B16+xMive0GqCOM52eQ6neaHJ2vpAN0vXyaD2Ps9VEXSet1iP6D3HNQynZhWxS3OkxDXkLjStvLmRfHuwGPZaJ1apm2ClFygiWZA/Tr/ImIiGssisesi+hSIbohlBCAVS78sRqlD5zMv4aDPQQRY4QhXScLSHpJj19OE3knioMc53C+1juG9R2LKqx2yw5xRg0kpqbJHreOjwmuhl4hNYlFcEcmCthQc4oyDrnlIpOqEJyMOUqzfsQ+wc3oTxs1w3vUtUzSekc5/HjsFWfCY/5HL9+9bv2wJ6cGIdTVihCzzaTkF4dueMp31EGyt1FcBi0RiQ2x+wY/4tp+MKt9II3o1JWjOs1AyfAs3WNpfcw/Qz1XjMyUDJFcJSQd9Ti9lnioU+dSYyoTTgwIOEX91I5qQ6YeORrEzY4kcBoRxQ3jTrb0MtH+6pVjUJKvxILOt08wSCqUiqxi0EtJw0MSuoo5lXmUapQn1G8v6F3lSRutLxCMp7XUXjfwLO2Td3VYTmyMhfQZ2NwvqrgFoY5GZPkkU1WeVOhLPXIbt2/XJ2b3mzyimKkFUYatlQMJLrgSZiyyYEHSo80zr1uqhPtePf3AauySvGjkfpEUy1inhyR60rG2VPbTWR3VM+z8BSqMoWG10B7ICcQtSQlnNQytG2OfqpsEKF5KanYVVc+ri8blORNzGQpt5YOunZUNvZCIx5y7962dVUsKlZQxU4bnPWVwpOk587VPJRa1R0lMxOZuo0QIdXQUDyUCVH1rZuw2yrkTZ4qf2eHvDXDzZeneCj1JkDNm6e1lzQJ/1CuERnjn0uleKNaCQEZhrw1wyGvWFzUZuFI6lxC/C4/Jj6fFb6hhiFvmjAXuUpF15wtqj6broci5FcWFC5JTFBEg4mHkopCqEI6GfJWDaNMVKgu6UPylWMozx7UdqKnSSMUELlGqR5Kus5oARJyZajyFhX7SsibCsoOzgG+yx1j6CWhohOSwcKc6TgiO4K5Qf3iI5KyeKlKwtnFMk4tkoVxudoo3yehtWnMUXq/k0Fp9oBVhZSpTVi4uQkSJYsbEQ6Kh5OV/MlUAec12YPg2bTc0nuY/uqhtHDNaAsgEfKmohwLOZRpBqWJhzIlNEvVu2ZpG1o61xPRQVhKXaf0Qt5iLEEscRQLtRGSvaKOMLpGdDggOgKRHiJp2OYihmo9XUki5MfWbKUTDxXxUU9rPcWPVAcLpZ2NdUaxinIWDQyhrar+5WHZUWxEFkKS3dADStJoJYkAxqtD3qAVtiRFzesyXgMzwvkYW3Yx/DGDHCV6TlB0zunGu3U2TBt6vPHn7m8QWpTEKwMPg7Mppde3jhZlJXk93YWYUWPiXdLGTteX2kjFSDZoR0LeyQVU68V/SrccLR9TS9sj54smt9evDErSY21dlEOQ/IdWtT1iYAluLWnC/SVH4uu5c9tunIij2ukTnsn8hgphhesZlFquHLXzI4rVTj16YcOgmuiqVHnLCOoIYKdCvUd39chd46GkmzoWhewrUPIio2YGpXIRy2YGIgnHh/y4LusgPF2rtmk0C3kTA0eIHCSzUGdNOCbycA7zRrAiJCEiWlAZGJSREP5ecDh+vZSSV7PFxK0beg0H1AWFhBHqHbNNp4+stj0lnZPHuUzdvslggqpQJ8tDfMo1Qy2uMkqLhPxCC45SHTTIYG2Ok3GWWYeSJhoKedMqfZAzgW/JoDQI7X3RIOG3BbLogEN5XN8GjK/Hf1cpPb0vKJXxiQgXmVyPqgi6wIKHMhgKISw5sNpVBEkVvDdEfUDadCRFWvNzwicq4Tf4I3C2zqtidg7aFfKOtqT40PVrMuelGpRKyNvE46iGZskLt45yqU0Myu9iPjxSfCjutO2mzKdGIfJICP/O3h37LFLuUzIojTyUNIfRs26iWkOyVs07z0jQjwpVlePD5iwRfjUae30oKqR9SH1imI0aTQwwNOgr1K5WB7jDWC3lCgF6ySx1IB7AXtmyUMYo18LGJBlEtPZQqvMGKbMEjHJLU7YlZwrNxPEsHyRqVagHVXp7lALWVwdMhEPtBJeRRmUOejFvH9w4/PfWmpaI1CYP5Cyl+KdzQ97qPulayZRSpVZ5a/4SrTCnqL/mUOq1gvusXhLiypRjeV1+ndCdmvLRN8D2DW13EI8Jg6IoEURJo6JPWauTH0AXAHXLoWRjrYCHftcz/EJqm0VR5Q0ZIZuBoaJC1Vy/8Ck5oJ2eQ0k010POV5OS9SYFcndTzqTWDYjaNJpMrjaaMLwUctAMSoNwkdaNZ+BI8atZDiVd7JRXQ4bT0oCkeleNPZSBrFyROE6TiGGHDAp5k0FpT2DPHBsikl3k6unvm7ZXZuFRqhZUk4HGGmm+1du9+IUngq0xG4J2kjzKMB7qh253tyrKkUXlt1hBtj5edaLRNFKJ73PHwEk9Y3V4tVoSyeN3DlNCS98HDOSRRB6lhC8alLDSp/UWpgSa7FImKdPCGSHenC3yJ6UGKwal8rnZrRgHAD6OF2LEwY9BXrfM0vZMPw55W7pm5GQ3MTmvBA6zRUhrD6VZ1bY6TWyKOxChaJXJ/dEUieG6UeegwVso5lfDpwEZBEISToJssysOA6OQtzqH0XMyBDsW2VNUPVoTakaTOxcPb7PjySY1XGw09mCTkCU6KEcWhX1rHAWGxUqkrxmSnHBJsiioNPP0Um4phYwPzwVWBimNTGu7mK9I4tDzJe14Ay25rvQs02u2ILbV8ha9ynml1CwjD2VzPT4c+EtMjQzFBk8JnI3VxilniQQeGH4SphfsC0uokahkq+fO8lDSMdHzXXhjsww9lFrIO+mhFAZlP/RQEpks5Se2KV6bqcPjOC6xFfeU/hpRvfCFalAWR5tQ2rRNd5+peZRa5wIyQvS8k0RQDem51ZA39Sg1Y06jTRT6UMi+SwxKfwPkAiV8of/Al9Vqt+y0HEozDyXpWiFLuQiNJ1dZubnKRlgzKKNhpfKPZBHCDqWy0sig1G5Cwu2FLRIwMRBzhKA4GfLLvYMRNwqJhEOoJBkfAGcVkoalDc06ouzaWKgHNXkeSWBX2UdmD6XfnpUmGyS6AlGYjDwmbXQog+L1jWrC+AZ4hJ6bMOx1oPxWajl2VrGMxQHJko4YVT5T84DPW8tiZUJ01VHSJKyEvOmYrxx3Ph4beVL7PJQWQ97a52xbu9ja9kz/QzMeLHq1xdxBkmkeHxxGxoG2bdKgpHnGxKBUnxVrYuqi2+z+oOvd7YU8Zl+4UppxZB6LUqSXLrJuEPJW9RPJoJzvGpguG5NpoShJuL66AMtUfVldxQ8i0CSUMA5RNy235ZqMPSzmSIKiFWYtMjVP75F5MpakNiEgDyUZk62jUdpiwu1Vc0sNngcp22ohYU0WLyPNdfi4aG/cNOA48Uwz9GrLCSUcT61AzRQEWmmdyt7czvVQaikI5ABwUaOQTB7KFmHzlhxKGUVOgxa8fd2gzBTLJ8/UyyL/K4ENthy84RmvvwO1KIcMyhJ/tblBGUvPodxuUO0UUquiKdydJQxK85A36eBpbeA6XTZI81AWaB5Kg4ufHtrJHEo3bCY3gAhD0sWZrxirpqt7CksUDxErNnvIOORNxpQm8LokpkyahjmUKT3LySg29lD6lSpEAL/KiWGxb5hJMr6MrfAKwfUcm4y/7HIxZKPPMRxUOj9QWCnh0Z/oQwE0O71pHkoKeQuNy0whCXUVH3R6RM7S964ySHXbTYIoEl6rVraYY8VABPBurYSy+TbFU2qGuGZaPJQ2Uw+lH++VHIBVeSOSPd6tGAdWcyhFRyz6TDavsrY90//Q7jWLXm2xcCtVWog6zbzmKTJDspsKG4wNyhq1IrNc1jQrzQzKoPCQyaVDkb9otslYUua8pMh6wDDkTZBqxlyPiSqH5hWje1vVJDaMPpBB6S4QupX1kitpSOsSjaBCnSNXZw0w91CqRTiUy/dzoFXbxdbhbu1zoFSvnHwlFcDoPKXUDwgHCWHkoWxSK8qHjodUl65xrRv2ttmsG5Rq6FnOLRTFq0aqGe2iuaHFCM/0maR01Ut6KCXF9qGK72p3gU4rkj5uUOpZyg9tlUR+xYN5v0TMyMUtDEoffIkwBoVqTA1K0qLUerEWOxKZJYNUQpFYSw4l4gha8FDSQ/9ztX1Sp+dQEuQZpGIYwuzGSsmhtOah9AFkrMZjphW74sanG4sEpw3CIco4w0I2g8K0P8dVr6lJyDvZwSLLK/RC9bcNoUr1OFIeojAoTSZ60k+c4DwOu20bg9cGTjSpOA8mJ8u11PZTG19rQgH4WxmUeQ65pU94m5CE5h3x4PbNEh4tPRJSreJhN+LVKkkIH39kJYStYinXJxnybsmhNBNuTs2rshbybl8OJdYtAZ6aZC5QzfRf2qNDSdC9PEA1KM08lCkhcri8poZQYzQmCjNFTiEZBmaRGS1cv2kVsrattWxQ0pynvF9nPGr7WE3hgUTQbUaLYs0rRve21jXNaM4THkrFYF3tKobDb/IsoFaOpMACiC5nZp9jXcrtTMLcSahdcKb2qvR8qdoMuXS4cbFSqxzKpIfSqLJa+3+FAyHVt1KQMcijhJmCQHI8arQtt9j8mdoetPm2sEwJ60cNPJQpVd6aNuf2Yy9CaJDSarfLDcorzj8dW3/6ALdPujD5mtvlxN2TL8GSOa9i9dzpeHbqZBQXpicCDx5YgpcevQ3l897G4tkv49Zrz4fdrj+UFWG7rtG1MiRhwiInnis6yPiCUEPexGj4Res1I6Fq0c9blXMpMQl500miMLeo8gZ5KE1kAlRmq4sHf1cZlHQBqeOzYlBaEfm10yqWVnSFA4W3ydRIVG8Oo/7KSeJRzCjcBwdEfoEtdtUDZhry1lbrJh5KyKhOaSO2OHs47GbSDOEA1maVIqq2sTQ0nOIxbFPzlZKhn0zjCZNBmd2qUw6EaK5yTBlueHF8Hjyz3Ya5gw+EVFthoehLQskPNnzd1AVrxtRrRuSUmXhgUsI3llb37cyhZJjkosWqQUn3Mi2MmxvMr99UQ85NKR4mC6hoBL/a+1Y8W3YUXHXbzBc6ai6g/dsPrY+DUA0B/b7iMuRIGJVqi9lvc8YYL6KTXjufUiAojsXgWINNyRxNMhAdFub4CodP6DZv8g4wDXlTxy5KNSJ+phQoOiIy/obvBmxckflN2zdAHqAYlIZFOfScoy9KNdDywY1C3vSsUM8jRYhMaVJz3NsT8qainLxi86hfe6Bx0zxaqkiwtQl5p6SNkbC55hjTOspRVDdcMtzyv9vhp81eE8biD6cfi6Ur0wXEp/ztQhx92IG4eNK9+N0FkzGgpBDPT5vc8g9tNmFMupwOnHTeJFx960M448SjMOmyc3X/14kbDBKJKfk5IintiowmEzXkTYxyxVWPp74h1xCX0jyURiFvMgLIoBSdcix7KIFZDZJwM2/Xa2/VEVJubsNJhNp8pRTlmFU8irw2ugFppWbpxlJXWxYEpwkKKy9ylCQnTcOx001ISemUcCyKcowNkOoUYdxFvmGwG4U4UgpikhO4SS5UhU35HMspOZ30PDOFLajK2+1Lkw2ikHcjVGM3kw4lISQlfOJLaq2xqjf8rmotSJOUGvKWLYa8lff5rekE1m2HbcFMuLenzy0Mo0vFOuD9JyFt32hte/WatTSHpeZc0hxp5pGPhPFD7mj4h+5mnhNJVKwFXrgVtnU/WxhHi0dJy6E0zBWksLfkwYogUO0pNJ7fQykeyhxlDjM0ylI9lLnDLXnWZvh2xcP28YjnlcJhMv/S3E9awDVxGzZc8jgadz0IiT0PUzyRi5UONG3Yth5yyRDlmWDiAdW65ZCHUooETcLMaj0AYTXk3S6DUisS62SDkqA0I9Wg1NM5TvNQSkqFN0E2U6R4kOV/tUOWjNeThcfuvh6T7ngUDU0tXp4cnxdnn3o0pjzwHL75YTF+Xl6O6/7+MA7Yezfsu4eS33j4Qftg3KihuOLmacIY/fybBbjviVdw3hm/hdNhzRDLRFz0v2y2ZFCOdMVMq5fIQ0meI6pIoypyQw9lJCjaLwphcyQQhjUPJXXmGfWjEwuN2jLtKKkGnNUcSoshbxHCLhvVLoNS0nI5rEz0VO2s9RU3DHmrf1PlFswMykAkiiDs2Cq7UQ1ziaRksrzWx9fkQbLWnocIbCh3Fup7MSiH0p0j5KKoAwSRR1XeWt6tTg6lMGwpbEFYCHl3KeKa8YgEfq0Vnen2RL2FiZhIxOGY9SrsVoxPhhHIwLJ5yXvKFPU+sxS+FNuHADJmQgF4tpjk6moLLG8OXDVbrO0/kzJJxnGo8yMdsZZDaThHBjDHOQhvUE61mSIDGWoUTaAOazkFsDfXGyfBUI9rtehnVfYgSx7K2e5huGXgb4VGsrvS2Pin8Dz1Il8s5Yux1x50KuL7HS3Os67ziD5Hej4Zem7Tu+VQDqVptIpQj0+q7wKDMkzavooh72jubIOyEihRDUoD2SAth5JkGovUDoQU1Y0UKl1/rLBDFtzdN1+CWV/Nx1ffLcLVfz0z+fqeu46By+kUr2usWb8Zm7dWYr+9dsHCn1di/z13wYo1G1Bd23LxzZn7I+79v8sxfvQwLFmZOYfEadc30uhvUbcXTnoA6WwnU8hTNShHOOP4IWKDy2CfzQlq9yRjkCobXx23w6WzeTwWQcjjgs8hiRzKKmTpjld7XftObfi8kAyPT++9RiQCjdACLc5EDJLOe2KRIBIen/gsoqpskNHYk5W3JFSu5mcYjScRaBDj0Cq8zcYeiYZhc3tgz/KK9znJ06fznkQsrGzjy0PUlycmNKP9RyMh0R92KXIgpeQ1OQ0+G9LytHtzEI/H4JQTumMhPvSMxr7Zp6BB8gmDMtN+45GgCHmTzEae045AgjzgcdQklJvaEY/ClvI+ORYR3WztYrIpRFxOwEWiup70a0zv2mjPNWN1+0Q4iJhkg7OoTLnvmmrNzyv1P26otjyeTMfWGWPf0e13dN8O9eFm9Xh709gzbZ/pb31l7KnEomHQ89OuFomZbR+NhiDbbHDPfBkOf4Px/RGPJudeV/WWTh07PWviTjecJMjuyUYiGoZohKPzXprzbsg7Ao6KNap3NWy4/0jIDxt57HIKxXHaDbaVY2FUqqlJqz1lsDd/beFzjEAetov42V25wfBZQ8bvKwMORaW0XTiEnA2ViBQNhuOnz9PmyLQx1WxFlKTwbDY46Fli+DwIis9QcnmERrLDbOxU6ErnlITL3Q7ja8BfL64BSnewdl7DiKstkMlD2ZnXTKyxGoldDlC2U3M6te3F/3XTs8SBhER3RELYMQNcEhplIEoSiPlqF7quMChP/s2h2GOX0Tj+3Ova/K20uADhSBSNTemrh6raepQWKR9WSXE+qmrSVzKacVlSXACszPx/S3P0m7En7A5scLqRizhy8jMLt1JXj42RmAgDum0y/JIDg3W2Fds7Ayhw+LFrPnnvwoi5sjE4P7MnsdFBuoMuFHmyRFN6Cn8bjTfT8Zht395t43YZYv0nJ1DqcUPyZNZcrJcSaPD4xGex0ZMtDKEig/3ThKNRGG4yHU9UimMz5QnGQpbGviURgzs7B67cfNBaqjTLDSkrs45iyOUAZRMWDBsLWjNSyMVo/9sTUXzpHYUFtkK4Uo5D7z3Vchxhrw/ugcMhN1RigMnYtyYS2Jw3DFnxGCKRYMb9BhySkA0ixhTkwSHJyLbXYK1DuRYHOW2wp1yXdN2up2PML0Q0rwT+5noM8Cjvz7R/vWNpz/Vltn3QIYF8pHlj9gSVM1DnKbP9bwo0wheoQ4G6XWdf7921fXv3XZid3a739aaxG23fnmuvM8bT2fumRl80exWEGi1tX1e5Hom6ChRtXWE+53ncYs4jXLVbO3XsfodNzHVlJaVozM1HU6t5pvV7t5EzwZeL0oJCrBddgSKG+98SDcGdV4BIfjEcjTUoMRn7l57huHTw6fjJNxzDTOZfMR45jqDbI/ZN+fhG25PRP23Yb+HM3S4Kp0o/eR6hsjHICTcABs/uzfXbES0sQ6HTBrfBdhXxKOy+fESKBsG9eaXhc4+oiQbRHGzGALdiNhmOXYphk6pNrW1ntH2jXYKmLOxoMv8cW2O473Bzct9FLgeZM8ntmx02VEk2DCopRZZ4RldhYLYXI9xx1JHXgyD5vq4wKAcNKMYdN/wVZ11ymzAcu5PKpiZE7E7EzrkZ9g+egi0lN8WeqzSBb6qrRmO9vtvd/uR1qNlDxiAXsC0UxxaDbTc64vCVyvBEFcNjWX0QW3WqTuMNdQh5XYjFosiSKaxqE+ONZtD8opUBnUzt761/N6I928r1DSJ0SEU2VQbbx+uqRTP6zf4A4t5cYZQZjb1IS2CmPNOt60FBF6PxyI1NkDavhn/dMlC2jdnYo6GAqEokDXGRQ9PUqL9vmxLyqfGoKzuDsROxpgacV3aaCHXYUmQn9N5D2ycGuxDLK4WntsJ87IFmEfK2ubxwhQIZt09kV4owjiBYn6z2XuMuEavwim1b2obtIkHUxWUkvPlA9Vax39bXgd610Z5rxur2CacSJqwtKBMLFtLxM9u/9Ob98AebEY1HLY1HGwfRmWPf0e13dN+1fr8wKq0eb28ae6btM/2tr4w9lVizYkg2btsAMvlN9z/rTfGt0sL+5bBavEFGE3Xc6sx7r14xDSqCEciwCwcAbU9kei8dp+zLw5ZAKBlGNtp/1N+IKKXfeHKRVVFuYc4L4NnRJ4swP1VtW5kjxWe0dY34bvisUXNEo/kDYF81H87mOtQtnI1Gk88ysW29SA+qq61B3OAZH2tugJxbJBqA5P0403Tsie/+B1v54ozzb8bnbzyGkPocMNs+Xt8S5jZ7jrX7mqloSS2oravBAEfL556oU66nrcFwsnA2GArAZZdRiXxIpGed8szvVINyz93GoKSoAJ+8/lDLDhx2/HLfCTj/zBNwzmW3iSrv3JzsNC9lSWE+KlWvZFV1PfbZfVzafrUq8Kpq/aReOvgoxfJLhyJGLvPKTS1jUJNK44EmY+HWeFzoWQ5yyaiMyIgYbFsdVR7qI11xxGVqbB9HRO2I04ZQACGbE267hNK4Hw0utxiv0f5b/91se6P36uJvFC5/w+3VG5xWdNrqyGj7ZMu/WBQxChfl5Rnvn15/+U4kyMWen28+9khIdH+IUxvIaNh4e9XLGC9Sxk76XYbbU54MTVLUYWI7+f0UdN9D+UQkkkspAT+thN9s7JRyQeHxAcPhXvYNApm29zdhWbaSkzLOHRcrWLq+1mWXifMVzVQRGg6KMBfoONctTU4cmcatdyztub5Mt1erUhNlo4GGGtjiUfP9q4VEWspAl1zv3bB9e/cdo/BbO97Xm8ZutH17rr3OGE+n71vNr4vXbAO8WZ27f22OVAuEOnXfVERJ29idsDmz4IyE0gyJNu+lObJgAKKqYDalHhnvvwnIzhPdaCjkHTQbO6UO2YaK/tXkz7Iyvwu2lJsea2qxn1y91fJnaSeDcreDEBMLWBMh93H7iR/d1ZuEoWq4b7I5Kjclw+imY2msRSIaMZyvk2gRM1IdsDKftsJw+5Sce3LYwOdt2V5V4IjaXUA8IQpz7EiIupEacthQekfIL9KuOt2gpNzII0+7PO21B++4BmvWbcbj/3obW7dXIxKNYuKBe+GjWUo/7dHDB2PIoFIsWKSECuYvXoGrLvw9igryUFOnFGocdtDewgBdtdakQk/TVdQSTDVUC9pQNkiFuoHotXJMRWt1d9XAuKgyM9Toi4QQsrkwNkvGwLgfP9rVcfYwkr8ektYYXg/tQi5VpAHMKvUk6gJA72luMJcM2hHUpHNL1cPa5ETC6X7lRrRU1UdJyK3bdultr15brtoKmAqS0HhG7SGSq0lPLmNJSTiAJocXG+Iu7O6lTrikUgAEsgsgNddlLimg4iPqelQ0CPj6PfQ4mgByyRBI65f09GgYpv2Qsbd+mVJQ5lVVHDoLKsRIJCCZFJ3sEKl9xUmyKxJE3LTYw5vsf203U9sgA2PYrkJyznTbFIeEpBWhWBy/RJXtJoiqa/osKVRvpVpexbb8W+T6ctFsJiFF8ztVg1NeqdWCwfawaI5QrLCEWmAqmWqi7gDUd5ye24QoRFWLcFsXfaqV3lRcTDqUGxzZ4jNyB5u6xqD0B4JYWZ5+kwSCIdQ1NCZff/3dzzDl+gtQ39CEJn8Ad910MeYvWi4Kcogv5v2IVWs34dG7rsM/HvqX8HjeePkf8OL0/yISjVkzKLUSeI1kQ3Vzg1IxJGXTlkI/+iWcttKGh0cksDVukiAbCSFoy8FEj/KxLyDZm94AGX1atbQe2k1HIr8UvrQyidDnXNdFlcZkRNIKWU0gtzS5FpVBSvFY60KrMypukSThyjclpcqYcqEsV+ol4nCneEAzfd5LE9nY3VsHaqqxJiSJdAMyijNCN/3ovZSf9fTXuhNSDdAm+p6uOGeYHWH1QuXLYvFDu/n0JdhpsdXZinCaAaD1FY+EzA1KMhZylLQwh5nIOs1PWnGIFWWOoLI/SdNdNB1/SISCJarGzrEQSqVnQDsNSsnfiPyfZpo7AFRPMklNCUdJZzNP1RW1co1pwvxk/HU2ZJiTwZ+V3dYtpj1DU/p5u9WW0AscOUAoiJzlc2G1s/iO6/ToMGXqc5BlGc8+MFmEv+fMXYjJdz+Z/HsikcCfrroD/7zlMnzw76nCIH3rg9m4/4lXzXeeX9zikSLJEtVDJpNuFl0QFmRGtO44mmFpxPu1EmY1OjE8n6QRGk08lIWi2m6DM19UefcGbBVr4ZJjxquLpIdymGKAWmj5ZFvxAxLVFuUw2gtNIE43ZF++CK8b3uZ0/jWhX6q8M4NyYB1KYVVqlbeVdm6WVuvqZE8TlK4kkSqou8SWjzO9dWiMA3ObyKDMg1SzTd9DSZ7SmgpVsL6LHoLtQX3wsEHJMBn4cbaS3mFQFLJDpLSBFNq7dRa68LhVD6WV+T3FKWPJuaCKgVv2UK78QSycLXe1ovk9y6vMMz5VL7mz0DoU6S3+u5OIulCw8hzbEcgDS81IWpPUOW4RNyc97aEuYGNWkdANzmrH59Nhg/L0C29OH18kipvveUp86bGlogp/vOL29v8zaraurbjyS1vcyUKDMGgpBKsZlEZtF1OJyBICss3cQ0k5CAC+F+2tTHT5ugn7vA9Qmp+PLZYMyqGQqrTaRGMcX/1Hyb/oCsNGVe6X88cja8lXmcPGGXS0LK2QUzuvWAl5h1QDsWqztaaEWtjCrKd0yI8ljiLcYF+HSAJ4qUpCzJur301Im2w2LEevgQ1Khul+kh4lEsEugWPTMqGGYdYnnFJmKKXGFO15EIu2SMQZoXWXsWpQkgA9fVl8dlBhpkwd2azqOe6IQbnNogZoVxIJdZ2HkqB6B+qBrvN/tY5zFPKmomWvHdjoKQXq26cF3Gd6eSdD3msXtwl7k4fSTNRag4pyrORQtgvhoVQ8X98X7iqqXvsMZARR4QAZZV21Omqvh5L6hGdlw7N5hfUb0cqElmJQtsdDKVVZCKenGH42M4MyHMBSV2lSRHZNxI4E5brqGZTaKnJjLzIo1WRuK20gGYbpJChPnLx7ucUiauEwM0C0uYO6naQoW5h6KJvrrInEax5KqyHv9kLzu1qQ0+lo+Z/bekFHrmAzMHcGbGt+6pr9f/8/YPYbbV8nj7VoJtLioRyXpZz3zdkDLEV9+6RBKWsG5dZyJdcstTDH47PcVaMq2j4PpSWiYdEph/gudwycvcEws4zcctH0hnFrIZ1QAG4rhpwWZrYy9tQVt6UcSnXf1dY8t6JvOQmxb15tMo4AVnjKEFPn6zVq729TD2VvyJ9MLcyhz8dKj3aGYTrXyBqgFFE61eYSumhze9Fgax5KbaHYZPG+pigh5UR2UaTCPncGMO+DLtk31i8Fpk9NkyDsUb5429o52hEoRW3Nj5n/JqK+LR7K0WrG3kbfIGutcvuiQSlyyChvhFZkVICR6qHMyrbmnqduJnU2XLolL+mp7BRkGWHZBqrZXegb2bc8lIT62fUOD6XqcdywzFqitNZ+0YqHUrs5qKjErF0gQSv6eR/CtmohLFH+M/Dk3yCZ9QgP+RH25GJ12CaMynVOJWFe1zir3CwqUi0Zwd0FPXCqSTOTYZgeMyjNnjXJHDk3JCs9orVngdX2f1Rc8/Dl+ovhDmKjiOQWRbOy06HnS7ka8dyZiVCamVL5TSlYA12KYVnlKzXu5d4dRTldBTVNF5BBSbl+Y/dp+SOFvEPNxtVuKiFZwkw/VT6374MyY2b2GMhlpOMkJ9sM9hl6lUGpeChttHq0QqqHkuLHRmiLDkoKt7RzGZgzXUmud1lJrpetFc0ILbA8LM0dAScaEFNzW0jmSVd+gr56E1++Ddi7oAc9wzDmBkDJEDHXmCphpHqYrHgdtZC3lfB4Wp5mLygUZHYMei6SOonqoSQ2RW2QJRuk1LqD/mRQipwRzaAk9+0BxygaUpQDkOWDvb7SslZSVzDTOwozBx9kvYCjN6EZWr3BoKScHDkBG0luSBYnV6qopve5qBrfAPJMUv5RTxv8NMmXDMY9Y89GmS2ChH2rch2rOT19Au3Bww8ShuletLxxKxqHKR6mdnko22NQMn2bQFNSb5lyKInNMdU0DAf6sYeSbg56kJFRSf0lqeVifVW7inK6DC30StVUfQ21+4LUUAN4TXQru5p1S4DnblGq3axIbtAE2FhrLYGcoOvESoV3V0J5SiVDsEiyYRH97houvNqWj4FhmJ2X9hiUKak9lvLzaGH73uOwbVoBqD2rmX5OsBnIL0nzUG5MKDUh/bcohwxKraJN86RpXkvyUOr02e723L+uUNzvasgoCwUgacUfPQlJP7VH4/Lbj4D3W3ROTSEXfk/nItLnTQsiMiypY0ROgbngMMMwTHsNSjIQtUJHq3mOy7+z1HWO6ScEm1M8lEpYcBOUqu9+GfJuGn8gEtS/u0411siTRuQVCRFsEqtO9pju6Zu8LxqUm1f23dAlhXHoy+r4v3rXejusrkJb9VFYnyoMy0aJPuSdKTzAMEw/pT0GpTbfJOJd02aS6VcGZUjzUEq+lHbFzv5lUAaGTVB0kjQNStLiotUWCZ2TZqGFHtRdTl82KJfOU776qlHZHpbNU7735LFqOatrf1a630w8VYS82aBkGMYULZJk2aAMpkumMUwqpEqieSi1ohxHbko74X5mUA747F/YUl+vdGfRoPA3eSipDSPJJ9RV9BKDsg/mUDLdi9ZCsXyRsjoMNMHZVGPc8YJhGCa1Ixc5L7IVuRdTA7SnawyY3gs9g6jA2e1FOKGkOmxy5Aljsr09zvuEQZkRCntTDqXaAcBuRVewK4moHWfI0M3N6dmxML0byhF99Krkr84X/44ctx2ctcQwjCnUnapiHSRSrYAFg5K6r7CHktFDy5f1+BCWVYPSXbRDi5C+a1CSoGvZCHHQUnuKOLoKVXBdoiRohmkHVH1pc1jRuWQYZqfn56+VL6tpO9+8r3zfGVKamA4ZlE1xoDIK+LNz0loV93+DUngCi8SPUnkX9b9sD/M/BRbO7ulRMAzDMAzDWEPTP/b68MwGCZ/WS8CR2Tubh7IGsDuAggGQuqp5fHvlbqhYiFeBDMMwDMP0MQ9lTUxCDVWHUivGdrZd7FM6lG3QNCnJQ9kbDEqGYRiGYZi+BDnCSKvUk1L7keXdobzb/mFQ1vSCHEqGYRiGYZg+rEUpyClo8VzuFCFvqqqmA45GIJFr1tPDLQMZhmEYhmH6sBYlCstEKiE2LN+JDEpNOijILesYhmEYhmE67KEct58SAl/3805mUH7z3g4ljjIMwzAMwzBQDEqvmkM5fj+lK2Gs/UXGfdugXLVA+c6V1QzDMAzDMDtmUBYNAnwFwKDRwPzPdmAnfbkoh2EYhmEYhumcHMrx+wPxmNJdaQdgg5JhGIZhGGanDnn7gL0PV4zJHez9zgYlwzAMwzDMzmxQOlxA6TBg4awd3g0blAzDMAzDMDsrQVVzsnYbsH7ZDu+GDUqGYRiGYZidvZ/3QvJOyju8GzYoGYZhGIZhdlYqNwJzpgM/zenQbvq2bBDDMAzDMAyz4yTiwLwP0VHYQ8kwDMMwDMN0CDYoGYZhGIZhmA7BBiXDMAzDMAzTIdigZBiGYRiGYToEG5QMwzAMwzBMh2CDkmEYhmEYhukQbFAyDMMwDMMwHYINSoZhGIZhGKZDsEHJMAzDMAzDdAgJpfvteONGhmEYhmEYZqeHPZQMwzAMwzBMh2CDkmEYhmEYhukQbFAyDMMwDMMwHYINSoZhGIZhGKZDsEHZC9j60wc49shf9vQwGIbpJvieZximv9HjBuWDd1yDFx68BX0dOg56SLT+GjG0DH1h3P+85bI2f7t78iXib7RNX2S/Pcdj04L38NKjt6Ev0Z/PSX+65/vTMfXVe0WPwoJc3HPzpfjh4xew7vt38NPMl/DaE7fjgL13RV9k0IBiTJtyFRZ++iLW//AOvv/oedxxw19RkJdj6f0H7b+7mDdyc7LR0/PaFeefnvY6Lazo9b76vN/ww7tYNOslvPHUHTjr5F9DkiTsrPS4QdmfmP31Aux11B/TvjZu2Y7ezpaKKpx87KHIcruSr7ldTpxy3OHYvLWyQ/t2OOzoKc4+5Ri88MaH+OW+EzCgpLBD+7LZbN06UXTlOWGYrrxXegPPTZ2M3XcZhatvfRATT74Y511zJ+bO/9myAdabGDZ4AD5+bRpGDhuEyyZPxSEnXowb73oCEw/cCzNeuh/5uT70FYKhMC47/zTk9aBh29nP+1/89gL84fLb8c0PPwsjnxZldvvOaVr1qqM+4uB98d6/7sXyr17Hkjmv4t+P3IbhQwYm/z5kUKlYERz3q4Pw1rN3oXze2/jszUfE6ro3EIlGUVVTn/aVSCTwmyN+gU9efwhrv/sP5n34LK67+Kw2F1xpcQFeeWwKyr99W2zz218f3G3j/nlFObZuq8ZxRx2UfO34ow4WRs2SlWvbfX5OOmYi/vPcPeJ4f3f8EegJvJ4snPSbiXhp+seY9dV8nHHSUW1W60cduj9mTn9EjPODl+7H+NHDktvQ9nScxxx+IOb853Gs//4dDC4r6XPnZPoz/8BdN13cxntDXo6JB+6Jnua7j57DheeelPbaZ28+jOsvOTv5O52rc049Bs9Pu1nc81/PeFqcl96KlWPqTRjdK9p9YOZRuvrCM7B49stY9c2bmHrblbj5qj+LY+4JyAv3y/12x10P/1sYkXTP/LRkNR574W18+sX3yW1onD/PfgUrv35T3Ce7jRuR3AedKxr/H047FvP/94K47p6670bk+Lzdfjx3T74U0WgMZ196G75dsARbtlXh828W4MyL/w9lpUW48Yo/iu1cTgduufrPYrzklf1mxtM4+5SjxbxM8zGx4qs3ejTC8fV3i1BVXYcrL/i97jY0z33+n8fFMdC9dPEfT0n+7aYr/4gPX57a5j1kB1x70Vnoief9tspaMV8/+vxbOP+au3DUxP1x5km/tnSdEUcfdgA+enWaeA4t+fxVMc/1VWy9bWJ7+uX3cNw514mbRU4kxIfb2jN00xV/xFMvvYujz7wKazduwRP/nNRrVwQH7rMbHr7zWjz32gwc8bvLcOM/HscZJ/1aTMCp3HDZH/DRrLk4+oyr8M5Hc/DkP2/AmJFDum2cb7w/E2epNwFBrvs3Z8zcofNz89XnieM9/NTLMGfuwm47hlTIqF2zfgvKN2zBf/47RxxPa2695nzcMe0FHH/udaitaxTGWKpH1ZPlxuXnn4a/3fEojjztctTUNnTrMXTGOXn93c+EV5MeNhqn/fZIMQl+/f1i9BVoEfbBp1/jqDOuxOyv5+Oxu6/vU56Z3oyVe8WIU48/HFddeAbuevhFHHv2tcLg+dPvj0NP4Q8E0ewPCMM39bpP5Zn7b0RxYR7OvWIKjj3nGixZvhbTn74r7ZqidKUTj5mIP199J865/O/C40lh9O6ExnPEwfvgxekfIRSOpP2NjBl6Vpz0m0PF74/84zqccuzh+L97n8Hhp14qnjX0WdDC9ILr7hbbTDzpYuFVu+2+Z9ATxBMJ3PPoSzj/rBOEMdyaPXYdjafvuwHv/+9LHHX6FXjgqdfFs1Fb5Lzz0RfYd4/xaYvmcaOHYcL4kXj34y/Q03zzw2IsXbk26Qgwu87IqfH8tFvEnHbMWVfjjItvwY9LVqGv0qusMDKoPp49D+s3VWDpynW4bsoj2G3cSIwbNTRtOzImaSW9duNWTH3yNQwdNAAjhw5CT/PrQw/A6rnTk19P338jrr/4bDz2r7fx1gezRfj7y29/wn2PvyJWvql88NnXeO3dT8Ux3f/Eq1i0bDX+cvaJ3Tb2//z3cxywz27CC0df+++9K97575wdOj/Pvvq+2G7T1u2orK5DT3D2qUeLYyI+n7sAub5s4ZlMZdrTr4vzsWLNBhEaKynMF95vDZfTicl3P4n5i1aIhy2Fa7qTzjgn9HfiNykFIGeceBSmtzJMeztvzpiF9/73pTjOex55Cb5sL/befVxPD6tfYOVeMeIvZ52AN977DG++P0vMXw8+84a4p3qKeDyBa257GL8/8VdY/tUbeP/Fe4Vna9eximfowL13w94TxuGiSf/E4mVrsG5jBe548AU0NDXjt0cfktyP2+XC1bdOE/fVdwuX4v/++TRO/s2hKCnK77ZjoTA3pdusWbc5499Xr9sswvh77z5WGJbXTXkY//v8W/GsoQXjjE+/FlGy+sYmsX11XYMwRJuaA+gpaHz0mf7t0nPa/I28kTTuh559U1xL02fMwr/e/BCX/vl34u+ryjcKg+3U4w5Pvud3xx+OBYtXiLmhN7Bm3WYMLSu1dJ2RY+n9T74Udgy9b9mq9cKT3lfJvHzrIUYOK8OkS8/FPnuMR2F+Lmw2xctCD9OV5RuT2y1bvT75c2VVrfheVJiHNesz33Tdxdz5i3HTXU8mfw8EQ5g1/VFhCKR6JGmCIO8XfWlGCt0QqSxYvFKsuroL8tCRkX7mSUcJ7xb9XFvfuEPnh26enmT08MHiRv7LtXcnHzAzPv1K5InNm78k7TPWqG9sRvmGzRib4hUOR6LiBu8pOuOc0DGQsUBeJ/Lw7bHLaOwyZpjIKetLLE+55+meaWzyi5U/0z33iuE+RgzBv6d/lPYaeVl6MqWCFlKzvvoBv9h3gvBo/Wrifrjsz0q0wetxI9ubhaVfvJb2HspXHpHi+SJPK3nyNWiOttvt4njJKOtNkFMlFotj3gJr56ynIW/2W8/chSdfejft9bEjh+KTOd+mvfbDT8tFCgk9N8k4Jq/sWScfLYxOgryyz7z8HnoLkiSB+lnvNn6E6XU2YdwovPrOJ+gv9CqD8t8P34bNFZWYdMej2FZVKy4gyl8jT1EqsVgs+bPWiFx7kPYkgWC4zSrJ683CA0+9ho9mzWuzfesQRk/zxvuf4a6bLhE/33xPi2Hc3vNDhnRPe1ycTgd+/OzfydcoAhyJxHDLP5+yvJ9QuHs9kl11Tl5751ORD0YhpjNPPkqEZSivrDeQSMhtUiYcjrbTEj0sU5Ehi2PtjVg9pt6A2b1CD3AJUq8ptGsPtJiiCAR9kfFBuWx/u+QcYfxur67D6Re2zVWjhUpvgp4ndA7GjhoqPHutoQVwXUMTQt0cPeko5PGdM2+hyLUlL2R7eO/jL3HL1eeJxXFWlktUwL//yVfoLYwZOUR4iLM9HtPrLNgLnjGdSa+Z5chtTyeCVpDf/7hMvEYu477OkhXlwgtg5o7fd89d8PaHn7f8vsf4tOKL7uDzbxaKh4ssy5gz98c+eX4ol/b0E36FKVOfwxfz0o+BZF1OOfawpCd73z3HCy8EQVWHo4YPFiGk3kRnnBMKPy5atgbnnvYbkU9JobveQk1dAwYUFyR/92V7MGzQAPRl+soxWblXNldUifGnRlMmjB+Vtm35+s3Ye8LYtPmLfu9trFq7UeRVUgFFaVEBYvG4oWLC4IElouJ9uxoFozk5Ho+L4+0uyFgkg/jPZxyPZ195P80JQaF3KnqkdKrlazYIp8pB++2Or75b1GY/VNRD2HvRIuzuh/8tFrqpn+fqdZtwQKs5jKSe1m7YKgxroqKyRnhiKXc3K8stPh+653oDhxywp0g5orSviu01ptcZRV6oWp/SRfoDvcagpJAjhfgot5Dy7uhmvvnqP6OvM+3pN/DSI7cJw+XDmXPFTTFh3EiMHzNc5FJqnPjrQ7B46WphGPzut0dgn93H4vrbH+nWsdLYKJlb+7kvnp+jDzsQebk+vP7eZ23yhCgMdvapx+DOB18Qv1NVYF19owhfUaEXHd//Zrf1AvQknXVOKD+XPJ3kPaacy97CN98vFgn3VH1Lq/ZJl52LeCLdG9nX6CvHZOVeOefS24QhOfmqP+H51z4QRlVqFThBckNTb71SLFrmL1qOk445VOQrbtyyDT0BLbQof/2N92aKB3azP4i9JozBZeedJsKpZIBQ+PpfD96Cfzz0osiPHlhSiKMOPUDcG1rKTjgSwcN3XiMK9yhn9x83XiTSRro73E2e4hkv3i90NO99/BVs2rJdFKLceu35wri697GXxVxAhuW0KVfj1vueETmKQwaVoLgwX4yZohg0f/z6sAMw6+v5CIUiPR5JooUuFdmk1go8/dJ7+OjVB3DNX8/EjE++wn577YLzzzwBk1tFZ9796Atcf+k5cDkc+PvU53pg9EqOPRn1tDArKSzAEYfsiyv/cjo+++J7vPXB5+LzNrvOKI9/+tP/wIbN20SOuMNuF1Xij7/4H/RFetygtEmSCGeRB+bSm+7DnTdchNlvP4by9VvEjfHO84rcQV+FVv5/uuoOUaV6+XmnIxqLCQ8ZPeBTmfrUazj52MNw982XCuOA9MZWr93U7eOlyTcTfeX8kEzGV9/9lDHp/L+z5uLy80/HbmNHJlfId9xwkUh8p0Rvquak89Pb6IxzQmGiOyb9VVRPUiiwN9zzxKMvvCV09mjRRefsvideEb/3NfriMVm5V8oGFOPKW6bh/649H+ee+ht8/f0ikcJD4ePUh/vwwQNx27V/gdvtFAbM9A9midzMnoAqm3/8eRUu+sPJGD50IJwOh6h0plw1knYh/nDF7WIROe32q1FUkIuq6np8u3AJqlOMRYoqUarSy49NEVW5M7/6QRTpdTdUzHHsudfib5eei6fvuxH5eT4xXgqBk0FCxiRx011P4KYr/ySaHxTk5wonxqPPTxd/o1xQKvygEPODt1+Ntz78HNfe9hB6mvuffDVZpU6Q9/jiG+4Ti7BrLjoTlVV1YpvWYfEPZ36Df9x0sTDaMqUCdAeUl7to1svC+0uFNstWrRPz7/QZs8XcbOU6ozzliybdi2svOlPcb83NAXy7cCn6KhJK99PSEHuEVx+fIm7cW3pRGI7p31AFK+my7XLoWb0uZ6qrIC26eR88g+PPvV5M2j1Jf7zn++MxdQTqGlJZXY+r/m8a+iKkQ0nh8aPPvLqnh8IwfYYeS6ignDWS2Tlo/z0y5nwwDNNxqICCwjI3Xv4HLPx5ZY8ak/3xnu+Px9ReKL+SvIEUhh0zYoiQgznsl/vgrQ/6R14YwzC9PORNLuC9JowVosw95bJmmP4OJbSTN5YS3//6t3/26Fj64z3fH4+pvVB4j/K+SNycJFEo9YKEtHdWA5thdlZ6POTNMAzDMAzD9G16j4YAwzAMwzAM0ydhg5JhGIZhGIbp/TmUV/zldBx/1MEYMwXOptQAAANJSURBVGKwEGal3sh3qbpMGm6XE3+//gIhIUA/k4gzSTRU17bIOJA8CuWEkYbjmnWbDCvwRgwtw6dvPCSa0e966NldfowMwzAMwzA7K93ioST1/hff/C9O+NMknHXJraLy9PUn7xDVgRpT/nahENq9eNK9+N0Fk0WHguenTc7Yio4ET42g/T/xz0n4Tu0ewjAMwzAMw/RxD+W5l09J+/2a2x7Cks9fxZ67jRE9PXN8XtFT9vLJU0WfYeK6vz+ML997UnRmILkTgkRDiaKCPOw2boTu/yOJlDXrNgsR3v332qVLj41hGIZhGGZnp0dyKHN92eJ7fUOT+L7nrmNEG6NUmQnqJkP9L6n1Unt7aZ5w9ETc3KpVE8MwDMMwDNNPdCglScLtk/4qelavLN8oXistLhDt4Fp3LamqrUdpUX67erg+dMc1uOKWB3Tb1TEMwzAMwzB93KCkPqO7jBmGU867sdP3ff9tV+Ddj78QYXSGYRiGYRimHxqUd910MY4+7ACc+pfJqKisSb5eWV0nKrtzc7LTvJQlhfmoVJuoW+GQA/fEMYf/Apf86VTxuyQBdrsdG+e/hxvufAxvvD+zk4+IYRiGYRiGcXSnMXnsrw7C6RdOxqat29P+tnj5GkSiUUw8cC98NGuueG308MEYMqgUCxatsPw/TvzTJNhtLWmhvznyl7j8vNNw0p8nYVuKAcswDMMwDMP0MYPy7psvxanHHYbzr7lL5DaWqHmRTc0BoUtJ319/9zNMuf4CUajT5A8IA3T+ouXJCm9NWzLbm4WSogLRM3bC+JHi9VXlmxCNxURldyrUYzchJ5K5mgzDMAzDMEwfNSjPO+N48f2d5+9pIx80fcYs8fOUqc9BlmU8+8BkVdh8oRA2T2Xq36/Ewfvvkfz9szcfEd8PPP4CURHOMAzDMAzDdD8SSveTe+D/MgzDMAzDMP0E7uXNMAzDMAzDdAg2KBmGYRiGYZgOwQYlwzAMwzAM0yHYoGQYhmEYhmE6BBuUDMMwDMMwTIdgg5JhGIZhGIbpEGxQMgzDMAzDMB2CDUqGYRiGYRimQ7BByTAMwzAMw3QINigZhmEYhmGYDsEGJcMwDMMwDNMh2KBkGIZhGIZh0BH+H9eXp3tXFJ6FAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 700x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Predictions plot\n",
    "# ==============================================================================\n",
    "fig, ax = plt.subplots(figsize=(7, 3))\n",
    "data_test['production'].plot(ax=ax, label='test', linewidth=1)\n",
    "predictions_backtest['pred'].plot(ax=ax, label='predictions', linewidth=1)\n",
    "ax.set_title('Energy production')\n",
    "ax.set_xlabel(\"\")\n",
    "ax.legend();"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "skforecast_py12",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.11"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": false,
   "sideBar": true,
   "skip_h1_title": true,
   "title_cell": "Tabla de contenidos",
   "title_sidebar": "Tabla de contenidos",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "165px"
   },
   "toc_section_display": true,
   "toc_window_display": false
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "position": {
    "height": "144.391px",
    "left": "1478px",
    "right": "20px",
    "top": "126px",
    "width": "350px"
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
